The Diagnostic Impact of Contrast-Enhanced Computed Tomography (CECT) in Evaluating Lymph Node Involvement in Colorectal Cancer: A Comprehensive Review.

Colorectal cancer (CRC) remains a significant global health burden, necessitating accurate staging and treatment planning for optimal patient outcomes. Lymph node involvement is a critical determinant of prognosis in CRC, emphasizing the importance of reliable imaging techniques for its evaluation. Contrast-enhanced computed tomography (CECT) has emerged as a cornerstone in CRC imaging, offering high-resolution anatomical detail and vascular assessment. This comprehensive review synthesizes the existing literature to evaluate the diagnostic impact of CECT in assessing lymph node involvement in CRC. Key findings highlight CECT's high sensitivity and specificity in detecting lymph node metastases, facilitating accurate staging and treatment selection. However, challenges such as limited resolution for small lymph nodes and potential false-positives call for a cautious interpretation. Recommendations for clinical practice suggest the integration of CECT into multidisciplinary treatment algorithms, optimizing imaging protocols and enhancing collaboration between radiologists and clinicians. Future research directions include refining imaging protocols, comparative effectiveness studies with emerging modalities, and prospective validation of CECT's prognostic value. Overall, this review stresses the pivotal role of CECT in CRC management and identifies avenues for further advancements in imaging-guided oncology care.

Study on the Prediction of Liver Injury in Acute Pancreatitis Patients by Radiomic Model Based on Contrast-Enhanced Computed Tomography.

OBJECTIVES: to predict liver injury in acute pancreatitis (AP) patients by establishing a radiomics model based on contrast-enhanced computed tomography (CECT). METHODS: a total of 1223 radiomic features were extracted from late arterial-phase pancreatic CECT images of 209 AP patients (146 in the training cohort and 63 in the test cohort), and the optimal radiomic features retained after dimensionality reduction by least absolute shrinkage and selection operator (LASSO) were used to construct a radiomic model through logistic regression analysis. In addition, clinical features were collected to develop a clinical model, and a joint model was established by combining the best radiomic features and clinical features to evaluate the practicality and application value of the radiomic models, clinical model and combined model. RESULTS: four potential features were selected from the pancreatic parenchyma to construct the radiomic model, and the area under the receiver operating characteristic curve (AUC) of the radiomic model was significantly greater than that of the clinical model for both the training cohort (0.993 vs. 0.653, p = 0.000) and test cohort (0.910 vs. 0.574, p = 0.000). The joint model had a greater AUC than the radiomics model for both the training cohort (0.997 vs. 0.993, p = 0.357) and test cohort (0.925 vs. 0.910, p = 0.302). CONCLUSIONS: the radiomic model based on CECT has good performance in predicting liver injury in AP patients and can guide clinical decision-making and improve the prognosis of patients with AP.

Role of Endoscopic Ultrasound in Staging and Vascular Assessment of Pancreatic Cancer.

Introduction Computed tomography (CT) of the abdomen with contrast stands as the gold standard for assessing pancreatic cancer, encompassing both staging and vascular analysis. However, not all patients are suitable candidates for contrast-enhanced CT (CECT) scans due to factors such as contrast agent allergies, pregnancy, renal impairment, radiation risks, and limited tissue sampling capability in CECT scans of the abdomen. In light of these challenges, this study evaluated the diagnostic capabilities of endoscopic ultrasound (EUS) compared to CECT for staging and vascular assessment of pancreatic cancer. Methods Fifty patients diagnosed with pancreatic cancer underwent evaluations using both CECT scans and EUS, focusing on staging and vascular invasion assessment. Vascular evaluation was carried out using a categorization system based on EUS findings, classifying them into three types based on the tumor-vessel relationship: Type 1 indicating clear invasion or encasement of a vessel by a tumor or contact with a vessel wall exceeding 180 degrees, Type 2 representing abutment, wherein a tumor contacts a vessel wall but at an angle less than 180 degrees, and Type 3 implying clear non-invasion, where a discernible distance exists between a tumor and a vessel. In this categorization, Type 1 and Type 2 indicated signs of vascular invasion, while Type 3 indicated vascular non-invasion. These findings were subsequently compared to the results from CECT scans. The endoscopist performing EUS was blinded to the CT outcomes prior to the examination. Results Regarding pancreatic cancer staging, EUS exhibited remarkable sensitivity, specificity, and accuracy rates of 100% according to the T criterion.As for vascular invasion assessment, EUS demonstrated sensitivity, specificity, and accuracy of 100%, 95.93%, and 96%, respectively, for venous invasion. For arterial invasion, the figures were 95.65% sensitivity, 100% specificity, and an overall accuracy of 99.5%. Conclusion EUS is an effective modality for evaluating both staging and vascular invasion in pancreatic cancer, boasting exceptional sensitivity, specificity, and accuracy rates. The findings are robust enough to consider EUS a viable alternative to CT scans in evaluation, with the added advantage of EUS offering tissue sampling capability.

Predictive Value of a Radiomics Nomogram Model Based on Contrast-Enhanced Computed Tomography for KIT Exon 9 Gene Mutation in Gastrointestinal Stromal Tumors.

OBJECTIVES: To establish and validate a radiomics nomogram model for preoperative prediction of KIT exon 9 mutation status in patients with gastrointestinal stromal tumors (GISTs). MATERIALS AND METHODS: Eighty-seven patients with pathologically confirmed GISTs were retrospectively enrolled in this study. Imaging and clinicopathological data were collected and randomly assigned to the training set (n = 60) and test set (n = 27) at a ratio of 7:3. Based on contrast-enhanced CT (CE-CT) arterial and venous phase images, the region of interest (ROI) of the tumors were manually drawn layer by layer, and the radiomics features were extracted. The intra-class correlation coefficient (ICC) was used to test the consistency between observers. Least absolute shrinkage and selection operator regression (LASSO) were used to further screen the features. The nomogram of integrated radiomics score (Rad-Score) and clinical risk factors (extra-gastric location and distant metastasis) was drawn on the basis of multivariate logistic regression. The area under the receiver operating characteristic (AUC) curve and decision curve analysis were used to evaluate the predictive efficiency of the nomogram, and the clinical benefits that the decision curve evaluation model may bring to patients. RESULTS: The selected radiomics features (arterial phase and venous phase features) were significantly correlated with the KIT exon 9 mutation status of GISTs. The AUC, sensitivity, specificity, and accuracy in the radiomics model were 0.863, 85.7%, 80.4%, and 85.0% for the training group (95% confidence interval [CI]: 0.750-0.938), and 0.883, 88.9%, 83.3%, and 81.5% for the test group (95% CI: 0.701-0.974), respectively. The AUC, sensitivity, specificity, and accuracy in the nomogram model were 0.902 (95% confidence interval [CI]: 0.798-0.964), 85.7%, 86.9%, and 91.7% for the training group, and 0.907 (95% CI: 0.732-0.984), 77.8%, 94.4%, and 88.9% for the test group, respectively. The decision curve showed the clinical application value of the radiomic nomogram. CONCLUSION: The radiomics nomogram model based on CE-CT can effectively predict the KIT exon 9 mutation status of GISTs and may be used for selective gene analysis in the future, which is of great significance for the accurate treatment of GISTs.

A Case of Pediatric Thyroid Abscess: A Rare Entity.

Acute Suppurative Thyroiditis (AST) is a rare, but potentially fatal emergency in the pediatric age group. With a mortality of 3.7% to 9% in AST, it is imperative to make a timely diagnosis and start treatment accordingly. In this case report, we discuss a case of thyroid abscess in a six-year-old, which was diagnosed on ultrasonography (USG)(machine: GE logic 9 USG, Milwaukee) and Contrast-Enhanced Computed Tomography (CECT) (machine: 32 slice GE revolution act machine, Milwaukee) of the neck. With this article, we attempt to stress upon the need for quick and accurate diagnosis and timely intervention to prevent complications as the condition is rare and unusual.

Deep learning-assisted diagnosis of parotid gland tumors by using contrast-enhanced CT imaging.

OBJECTIVES: Imaging interpretation of the benignancy or malignancy of parotid gland tumors (PGTs) is a critical consideration prior to surgery in view of therapeutic and prognostic values of such discrimination. This study investigates the application of a deep learning-based method for preoperative stratification of PGTs. MATERIALS AND METHODS: Using the 3D DenseNet-121 architecture and a dataset consisting of 117 volumetric arterial-phase contrast-enhanced CT scans, we developed a binary classifier for PGT distinction and tested it. We compared the discriminative performance of the model on the test set to that of 12 junior and 12 senior head and neck clinicians. Besides, potential clinical utility of the model was evaluated by measuring changes in unassisted and model-assisted performance of junior clinicians. RESULTS: The model finally reached the sensitivity, specificity, PPV, NPV, F1-score of 0.955 (95% CI 0.751-0.998), 0.667 (95% CI 0.241-0.940), 0.913 (95% CI 0.705-0.985), 0.800 (95% CI 0.299-0.989) and 0.933, respectively, comparable to that of practicing clinicians. Furthermore, there were statistically significant increases in junior clinicians' specificity, PPV, NPV and F1-score in differentiating benign from malignant PGTs when unassisted and model-assisted performance of junior clinicians were compared. CONCLUSION: Our results provide evidence that deep learning-based method may offer assistance for PGT's binary distinction.

Specific imaging features indicate the clinical features of patients with hepatic perivascular epithelioid cell tumor by comparative analysis of CT and ultrasound imaging.

Objective: The objective of the study was to explore the CT and ultrasound features and clinical significance of perivascular epithelioid cell tumor (PEComa) of the liver. Methods: Eleven hepatic PEComa patients treated in our hospital were retrospectively analyzed based on the characteristics of the imaging results of the patients, including conventional ultrasound, CDFI, contrast-enhanced ultrasound (CEUS), and contrast-enhanced CT (CECT). Results: CT scans showed that all lesions were hypodense. Ultrasonography showed that lesions were either hyperechoic (4/11, 36.36%), hypoechoic (4/11, 36.36%), isoechoic (1/11, 9.09%), or heterogeneously echoic (2/11, 18.18%). CDFI showed that most of the lesions had an abundant blood supply (9/11, 81.82%). Whether on CT scan or ultrasonography, the margins of the lesions were dominated by clear margins. Ultrasonography revealed more features: hyperechoic patterns around lesions (3/11, 27.27%) and lateral shadow (5/11, 45.45%). The CDFI showed that large blood vessels were observed around the lesions (9/11, 81.82%). CECT shows two enhancement patterns: "fast in and fast out (FIFO)" (8/11, 72.72%) and "fast in and slow out (FISO)" (3/11, 27.27%). CEUS shows that all lesions had the enhancement pattern of "FISO," which was different from CECT. All lesions displayed rapid enhancement during HAP in CEUS during 7-20 s. Four patients (36.36%) washed out at 60-180 s, another four (36.36%) washed out at 180-300 s, and the remaining three patients (27.27%) showed no signs of washout even at 360 s. Conclusion: Some imaging features, such as clear margins, peripheral hyperechoic around the lesion, lateral shadow, the large blood vessels around lesions, and the "FISO" enhancement pattern, may indicate expansive growth of the tumor and be helpful in the diagnosis of PEComa. Ultrasound images may provide more details for clinical reference.

The predictive potential of contrast-enhanced computed tomography based radiomics in the preoperative staging of cT4 gastric cancer.

Background: The accuracy of preoperative staging is crucial for cT4 stage gastric cancer patients. The aim of this study was to develop the radiomics model and evaluate its predictive potential for differentiating preoperative cT4 stage gastric cancer patients into pT4b and no-pT4b patients. Methods: A multicenter retrospective analysis of 704 gastric cancer patients with preoperative contrast-enhanced computed tomography (CE-CT) staging cT4 between January 2008 and December 2021. These patients were divided into the training cohort (478 patients, the Affiliated Hospital of Qingdao University) and validation cohort (226 patients, the Weihai Wendeng District People's Hospital). According to the pathological stage of the tumors, the patients were divided into pT4b or no-pT4b stage. In the training cohort, the clinical and radiomics features were analyzed to construct the clinical model, tri-phase radiomics signatures and nomogram. Two kinds of methods were employed to achieve dimensionality reduction: (I) the least absolute shrinkage and selection operator (LASSO); and (II) the minimum redundancy maximum relevance (mRMR) algorithms. We utilized Logistic regression, support vector machine (SVM), Decision tree and Adaptive boosted tree (AdaBoost) algorithms as the machine learning classifiers. The nomogram was constructed on the clinical characteristics and the Rad-score. The performance of the models was evaluated by receiver operating characteristic (ROC) area under the curve (AUC), Decision Curve Analysis (DCA) curve and calibration curve. Results: The 345 pT4b and 359 no-pT4b stage patients were included in this study. In the validation cohort, the AUC of the clinical model was 0.793 (95% CI: 0.732-0.855). The tri-phase radiomics features combined with the SVM algorithm was the best radiomics signature with an AUC of 0.862 (95% CI: 0.812-0.912). The nomogram was the best predictive model of all with an AUC of 0.893 (95% CI: 0.834-0.927). In the training and validation cohorts, the calibration curves and DCA curves of the nomogram showed satisfactory result. Conclusions: CE-CT-based radiomics nomogram offers good accuracy and stability in differentiating preoperative cT4 stage gastric cancer patients into pT4b and non-pT4b stages, which has a great clinical relevance for selecting the course of treatment for cT4 stage gastric cancer patients.

The diagnostic performance of contrast-enhanced ultrasound versus contrast-enhanced computed tomography for pancreatic carcinoma: a systematic review and meta-analysis.

Background: Pancreatic carcinoma is a highly fatal disease, and early diagnosis is of vital importance. This meta-analysis aimed to compare the diagnostic performances of contrast-enhanced ultrasonography (CEUS) against contrast-enhanced computed tomography (CECT) for pancreatic carcinoma, using pathological results or alternative imaging modality as the gold standard. Methods: A thorough search was conducted in PubMed, EMBASE, Web of Science and Cochrane Library databases. Two investigators selected the studies and extracted the data independently. A bivariate mixed-effects regression model was used to calculate the pooled data. Subgroup analysis and meta-regression were performed to explore the causes of heterogeneity. Results: A total of 1,227 records were identified, of which 7 articles with 588 patients were assessed for eligibility. The overall sensitivity, specificity of CEUS and CECT with their 95% confidential intervals (95% CI) were 0.91 (0.85-0.94) and 0.88 (0.81-0.92), 0.83 (0.70-0.91) and 0.87 (0.73-0.94), respectively. The area under curve (AUC) of CEUS and CECT were 0.94 and 0.93. Subgroup analysis showed CEUS may be good at diagnosing lesions with diameters less than 2 cm. Tumor features, region and study type were the main causes of heterogeneity. Conclusions: CEUS has a satisfying diagnostic performance for pancreatic carcinoma and it has high sensitivity for small pancreatic carcinomas (≤2 cm); besides, it performs well in discriminating pancreatic cancer from chronic pancreatitis. Therefore, CEUS can be a useful supplement to CECT.

A radiogenomics biomarker based on immunological heterogeneity for non-invasive prognosis of renal clear cell carcinoma.

Background: Tumor immunological heterogeneity potentially influences the prognostic disparities among patients with clear cell renal cell carcinoma (ccRCC); however, there is a lack of macroscopic imaging tools that can be used to predict immune-related gene expression in ccRCC. Methods: A novel non-invasive radiogenomics biomarker was constructed for immune-related gene expression in ccRCC. First, 520 ccRCC transcriptomic datasets from The Cancer Genome Atlas (TCGA) were analyzed using a non-negative matrix decomposition (NMF) clustering to identify immune-related molecular subtypes. Immune-related prognostic genes were analyzed through Cox regression and Gene Set Enrichment Analysis (GSEA). We then built a risk model based on an immune-related gene subset to predict prognosis in patients with ccRCC. CT images corresponding to the ccRCC patients in The Cancer Imaging Archive (TCIA) database were used to extract radiomic features. To stratify immune-related gene expression levels, extracted radiogenomics features were identified according to standard consecutive steps. A nomogram was built to combine radiogenomics and clinicopathological information through multivariate logistic regression to further enhance the radiogenomics model. Mann-Whitney U test and ROC curves were used to assess the effectiveness of the radiogenomics marker. Results: NMF methods successfully clustered patients into diverse subtypes according to gene expression levels in the tumor microenvironment (TME). The relative abundance of 10 immune cell populations in each tissue was also analyzed. The immune-related genomic signature (consisting of eight genes) of the tumor was shown to be significantly associated with survival in patients with ccRCC in TCGA database. The immune-related genomic signature was delineated by grouping the signature expression as either low- or high-risk. Using TCIA database, we constructed a radiogenomics biomarker consisting of 11 radiomic features that were optimal predictors of immune-related gene signature expression levels, which demonstrated AUC (area under the ROC curve) values of 0.76 and 0.72 in the training and validation groups, respectively. The nomogram built by combining radiomics and clinical pathological information could further improve the predictive efficacy of the radiogenomics model (AUC = 0.81, 074). Conclusions: The novel prognostic radiogenomics biomarker achieved excellent correlation with the immune-related gene expression status of patients with ccRCC and could successfully stratify the survival status of patients in TCGA database. It is anticipated that this work will assist in selecting precise clinical treatment strategies. This study may also lead to precise theranostics for patients with ccRCC in the future.

Gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs): a radiomic model to predict tumor grade.

PURPOSE: The aim of this single-center retrospective study is to assess whether contrast-enhanced computed tomography (CECT) radiomics analysis is predictive of gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) grade based on the 2019 World Health Organization (WHO) classification and to establish a tumor grade (G) prediction model. MATERIAL AND METHODS: Preoperative CECT images of 78 patients with GEP-NENs were retrospectively reviewed and divided in two groups (G1-G2 in class 0, G3-NEC in class 1). A total of 107 radiomics features were extracted from each neoplasm ROI in CT arterial and venous phases acquisitions with 3DSlicer. Mann-Whitney test and LASSO regression method were performed in R for feature selection and feature reduction, in order to build the radiomic-based predictive model. The model was developed for a training cohort (75% of the total) and validated on the independent validation cohort (25%). ROC curves and AUC values were generated on training and validation cohorts. RESULTS: 40 and 24 features, for arterial phase and venous phase, respectively, were found to be significant in class distinction. From the LASSO regression 3 and 2 features, for arterial phase and venous phase, respectively, were identified as suitable for groups classification and used to build the tumor grade radiomic-based prediction model. The prediction of the arterial model resulted in AUC values of 0.84 (95% CI 0.72-0.97) and 0.82 (95% CI 0.62-1) for the training cohort and validation cohort, respectively, while the prediction of the venous model yielded AUC values of 0.7877 (95% CI 0.6416-0.9338) and 0.6813 (95% CI 0.3933-0.9693) for the training cohort and validation cohort, respectively. CONCLUSIONS: CT-radiomics analysis may aid in differentiating the histological grade for GEP-NENs.

Obstructive Jaundice as the Initial Manifestation of Gastric Adenocarcinoma.

A 52-year-old female presented with epigastric pain, yellowing of the sclera, and vomiting for three weeks. Laboratory investigations revealed markedly elevated serum bilirubin and alkaline phosphatase levels, accompanied by a modest rise in transaminases. A clinical diagnosis of obstructive jaundice was established. Ultrasound of the abdomen depicted a mass in the region of the head of the pancreas. Contrast-enhanced computed tomography (CECT) of the abdomen revealed an infiltrative gastric mass spreading across the gastroduodenal junction and involving the ampulla of Vater. Owing to comorbid conditions and widespread lymphadenopathy, a palliative gastrojejunostomy with excision biopsy was performed. Histopathology confirmed an undifferentiated gastric adenocarcinoma.

Multi-Phase CT-Based Radiomics Nomogram for Discrimination Between Pancreatic Serous Cystic Neoplasm From Mucinous Cystic Neoplasm.

PURPOSE: This study aimed to develop and verify a multi-phase (MP) computed tomography (CT)-based radiomics nomogram to differentiate pancreatic serous cystic neoplasms (SCNs) from mucinous cystic neoplasms (MCNs), and to compare the diagnostic efficacy of radiomics models for different phases of CT scans. MATERIALS AND METHODS: A total of 170 patients who underwent surgical resection between January 2011 and December 2018, with pathologically confirmed pancreatic cystic neoplasms (SCN=115, MCN=55) were included in this single-center retrospective study. Radiomics features were extracted from plain scan (PS), arterial phase (AP), and venous phase (VP) CT scans. Algorithms were performed to identify the optimal features to build a radiomics signature (Radscore) for each phase. All features from these three phases were analyzed to develop the MP-Radscore. A combined model comprised the MP-Radscore and imaging features from which a nomogram was developed. The accuracy of the nomogram was evaluated using receiver operating characteristic (ROC) curves, calibration tests, and decision curve analysis. RESULTS: For each scan phase, 1218 features were extracted, and the optimal ones were selected to construct the PS-Radscore (11 features), AP-Radscore (11 features), and VP-Radscore (12 features). The MP-Radscore (14 features) achieved better performance based on ROC curve analysis than any single phase did [area under the curve (AUC), training cohort: MP-Radscore 0.89, PS-Radscore 0.78, AP-Radscore 0.83, VP-Radscore 0.85; validation cohort: MP-Radscore 0.88, PS-Radscore 0.77, AP-Radscore 0.83, VP-Radscore 0.84]. The combination nomogram performance was excellent, surpassing those of all other nomograms in both the training cohort (AUC, 0.91) and validation cohort (AUC, 0.90). The nomogram also performed well in the calibration and decision curve analyses. CONCLUSIONS: Radiomics for arterial and venous single-phase models outperformed the plain scan model. The combination nomogram that incorporated the MP-Radscore, tumor location, and cystic number had the best discriminatory performance and showed excellent accuracy for differentiating SCN from MCN.

Surveillance for Patients with Oral Squamous Cell Carcinoma after Complete Surgical Resection as Primary Treatment: A Single-Center Retrospective Cohort Study.

BACKGROUND: The surveillance methods oral squamous cell carcinoma (OSCC) patients may be chosen by considering the risk for recurrence, and it is important to establish appropriate methods during the period in which latent/dormant cancer cells become more apparent. To investigate the appropriate surveillance of patients with OSCC based on the individual risk for recurrence and/or metastasis, we performed a retrospective cohort study after the complete surgical resection of OSCC as the primary treatment. METHODS: The study was performed in 324 patients with OSCC who had been primarily treated with surgery from 2007 to 2020 at our hospital. We investigated the period, timing, and methods (visual examination, palpation and imaging using FDG-PET/CT or CECT) for surveillance in each case that comprised postsurgical treatment. RESULTS: Regarding the time to occurrence of postsurgical events, we found that half of cases of local recurrence, cervical lymph node metastasis, and distant metastasis occurred within 200 days, and 75% of all of these events occurred within 400 days. However, the mean time for second primary cancer was 1589 days. The postsurgical events were detected earlier by imaging examinations than they were by visual examination and palpation. CONCLUSIONS: For the surveillance of patients with OSCC after primary surgery, it is desirable to perform FDG-PET/CT within 3-6 months and at 1 year after surgery and to consider CECT as an option in between FDG-PET/CT, while continuing history and physical examinations for about 5 years based on individual risk assessment.

Pleuropulmonary blastoma: A report of three cases and review of literature.

Pleuropulmonary blastoma is a rare and highly aggressive pulmonary malignancy in children. Clinically, the malignancy is often mistaken for symptoms of respiratory tract infection or pneumothorax. The neoplasm is histologically characterized by primitive blastema and a malignant mesenchymal stroma that demonstrates multidirectional differentiation. The patients with PPB are managed by multimodal therapy. We present a report of 3 cases of histopathologically diagnosed pleuropulmonary blastoma. The patients presented with chief complaints of difficulty in breathing, cough, fever and chest pain. Radiographs of the patients showed partial to complete opacification of hemithorax. Contrast enhanced computed tomography scans revealed large well defined heterogenously enhancing solid mass lesions in the hemithorax. Knowledge of types, imaging findings, staging and association with other tumors is crucial for correct diagnosis of pleuropulmonary blastoma and subsequent adequate management.

Contrast-enhanced computed tomography prior to percutaneous transthoracic needle biopsy reduces the incidence of hemorrhage.

BACKGROUND: Hemorrhage is the second most common complication of percutaneous transthoracic needle biopsy (PTNB), and at present, there is no effective prevention strategy. Contrast-enhanced computed tomography (CECT) has the advantage of clearly visualizing blood supply within the lesion and aiding in the imaging of blood vessels, which can reduce hemorrhage complicating PTNB. As no large-sample studies were evaluating whether CECT could reduce hemorrhage, we conducted the present retrospective study. METHODS: From November 2011 to February 2016, 1,282 biopsies at Jinling Hospital were retrospectively reviewed; 555 underwent CECT, and 727 underwent non-contrast computed tomography (CT). Factors associated with hemorrhage were defined, and hemorrhage rates were compared between the 2 groups. RESULTS: We found that pre-biopsy CECT was associated with a reduced incidence of biopsy-related hemorrhage compared to non-contrast CT (16.4% vs. 23.1%, P=0.003). Propensity score matching (PSM) analysis also showed that the incidence of hemorrhage in the CECT group was lower than that of the non-contrast CT group at a ratio of 1:1 (P=0.039), 1:2 (P=0.028), or 1:3 (P=0.013). In the multivariate analysis, CECT before PTNB was found to be significantly associated with a reduced risk of hemorrhage [odds ratio (OR): 0.671, 95% confidence interval (CI): 0.499-0.902, P=0.008]. Puncture position, lesion size, depth of needle tract, and the number of punctures were also found to be associated with hemorrhage (all P<0.05). CONCLUSIONS: Compared with non-contrast CT, CECT significantly reduced the risk of post-biopsy pulmonary hemorrhage, which suggests that CECT should be performed before PTNB.

Diagnostic accuracy of contrast enhanced computed tomography (CECT) in detection of necrosis in acute pancreatitis by taking surgical findings as gold standard.

OBJECTIVE: To determine the diagnostic accuracy of contrast-enhanced computed tomography in the detection of necrosis in acute pancreatitis by taking surgical findings as the gold standard. METHODS: The descriptive cross-sectional study was conducted at Radiology and Surgery departments of the Jinnah Postgraduate Medical Centre, Karachi, from January 1 to June 30, 2016, and comprised patients of either gender having severe clinical pancreatitis with symptoms lasting >72 hours without showing improvement. Computed tomography scan was performed with slice thickness of 3mm. Multiple detector scan of abdomen with contrast was done. Data was analysed using SPSS 19. RESULTS: Of the 191 patients, 97 (50.8%) were female, and 129 (67.50%) were aged >40 years, with an overall mean age of 39.65±11.67 years. Mean duration of the symptoms was 85.61±6.41 hours. Contrast-enhanced computed tomography scan's sensitivity was 71.4%, specificity 87%, positive predictive value 83.33%, negative predictive value 76.99% and over all diagnostic accuracy was 79.5%. CONCLUSIONS: The diagnostic accuracy of contrast-enhanced computed tomography was found to be high in detecting necrosis in acute pancreatitis cases.

Effectiveness of Contrast-Enhanced Ultrasonography for the Characterization of Small and Early Stage Pancreatic Adenocarcinoma.

The purpose of this retrospective study is to evaluate the effectiveness of contrast-enhanced ultrasonography for the characterization of small and early stage pancreatic adenocarcinoma. Contrast-enhanced ultrasonography and contrast-enhanced computed tomography (CT) were performed in 200 cases, with pancreatic hypoechoic regions detected with ultrasonography. Assuming that hypo-enhancement was indicative of pancreatic adenocarcinoma, the sensitivity of each imaging modality was calculated. The sensitivities of contrast-enhanced ultrasonography and contrast-enhanced CT to characterize adenocarcinoma were 97.0% and 77.0% (p < 0.0001) for all 100 adenocarcinoma cases, 100% and 76.7% (p = 0.0016) for 43 small (≤20 mm) cancers, 100% and 58.3% (p = 0.0253) for 12 smaller (≤10 mm) cancers and 100% and 72.2% (p = 0.0016) for 36 stage IA cancers, respectively. The sensitivity of contrast-enhanced ultrasonography was sufficiently high and significantly superior to that of contrast-enhanced CT. Contrast-enhanced ultrasonography is a sensitive tool for selecting highly possible pancreatic adenocarcinoma lesions without overlooking early stage tiny adenocarcinomas among a large number of hypoechoic lesions detected with ultrasonography.

Heterotopic accessory spleen with squamous epithelial cyst in pancreas mimicking other pancreatic tumor: a case report.

A 49-year-old female undergoing a periodic health examination at other hospital revealed a mass in the tail of pancreas. The patient denied any personal history of surgery except subtotal hysterectomy because of multiple myomas in uterus 7 years ago, family history of abdominal cancer and trauma. Physical examination and laboratory finding (including tumor marker) were unremarkable. Chest X-ray result was normal. Contrast enhanced ultrasound (CEUS) examination showed a well-defined hypoechoic pancreatic mass which was suggestive of solid pseudopapillary tumor. Contrast enhanced computed tomography (CE-CT) of the abdomen revealed a mass of hypodensity suggestive of intraductal papillary mucinous neoplasm. Because of the risk of bleeding and exclusion of surgical contraindications, patient underwent laparoscopic surgery. Intraoperatively, a solid mass was identified in the tail of pancreas, the intraoperative frozen pathological examination suggested a heterotopic accessary spleen (HAS) with squamous epithelial cyst. Partial pancreatectomy was performed. The uniqueness of this case is that the spleen can be ectopic to the pancreas, what is even more unexpected is that the HAS undergone cystic change. When encountering a pancreatic mass, we need to think about the possibility of HAS. In conclusion, it is important to diagnose HAS with squamous cyst in the pancreatic tail presenting as other pancreatic masses.