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Basal cell carcinoma is the most common cancer worldwide. Most of basal cell carcinoma can be detected in the early stages and are generally well controlled with local resection. Despite the high incidence of BCC, intramucosal BCC is a very rare clinical entity. We hereby present a rare case report of pigmented BCC on soft palate and review the literature of this entity.

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Background: Sagittal split ramus osteotomy is an established procedure used in oral and maxillofacial surgery. Major bleeding is representative intraoperative complication involves vessels such as the inferior alveolar, facial, and maxillary arteries and accompanying veins, in particular the retromandibular vein (RMV). We previously described the RMV course patterns using embalmed cadavers. However, owing to the possible influence of formalin fixation and unclear skeletal classification of the jaws, the present study aimed to use contrast-enhanced computed tomography to confirm the RMV in patients with defined jaw deformities. Methods: Twenty patients with orthognathic jaw deformities (40 sides) were included. The RMV and the lateral and posterior views of the mandible were evaluated using contrast-enhanced computed tomography. Course patterns and RMV positions were classified as previously reported. Results: Three patterns were identified in the lateral view. Type A: RMV posterior to the posterior border of the ramus (n=25; 62.5%). Type B: adjoining the posterior border of the ramus (n=12; 30.0%). Type C: anterior to the posterior border of the ramus (n=3; 7.5%). Five course patterns were identified in the posterior view. Pattern I: rectilinear course running medial to the posterior border of the ramus (n=3; 7.5%). Pattern II: diagonal course running medially from immediately posterior to posterior border of the ramus (n=11; 27.5%). Pattern III: rectilinear course running immediately posterior to the posterior border of the ramus (n=12; 30.0%). Pattern IV: diagonal course running from lateral to medial relative to the posterior border of the ramus (n=8; 20.0%). Pattern V: diagonal course running from lateral to immediately posterior relative to the posterior border of the ramus (n=6; 15.0%). In the no-course pattern group, the RMV inferior to the lingula was lateral to its position and superior to that of the lingula. In half of the cases, the left and right sides exhibited different running patterns. We observed no correlation between the skeletal patterns of jaw deformities and the course of the RMV. Conclusions: Type B/Pattern II that runs in a straight line bordering the posterior margin of the ramus requires the most attention during surgery. These findings suggest the possibility of predicting intraoperative bleeding risk.

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OBJECTIVES: The study aims to compare retrospectively three clinically applied methods for the diagnostic performance of cystic renal masses (CRMs) by contrast-enhanced ultrasound (CEUS) and contrast-enhanced computer tomography (CECT) with Bosniak classification system. METHODS: A total of 52 cases of Bosniak II-IV CRMs in 49 consecutive patients were diagnosed from January 2013 to July 2022 and their data were analyzed. All patients had been subjected to CEUS and CECT simultaneously. Pathological diagnoses and masses stability were used as standard references to determine whether lesions were malignant or benign. Then 49 CRMs only with pathologic results were classified into group 1 and 2. RESULTS: A total of 52 CRMs in 49 enrolled patients were classified into 8 category II, 16 category IIF, 15 category III, and 13 category IV by CEUS (EFSUMB 2020), 10 category II, 13 category IIF, 16 category III, and 13 category IV by CEUS (V2019), while 15 category II, 9 category IIF, 13 category III, and 15 category IV by CECT (V2019). Pathological results and masses stability longer than 5 years follow-up performed substantially for CEUS (EFSUMB 2020), CEUS (V2019), and CECT (V2019) (kappa values were 0.696, 0.735, and 0.696, respectively). Among 49 pathologic approving CRMs, wall/septation thickness ≥4 mm, wall/septation thickness, presence of enhancing nodule and the diameter were found to be statistically significant for malignancy. Twenty-two malignant masses were correctly diagnosed by CEUS (V2019), while 21 malignant masses were both correctly diagnosed by CEUS (EFSUMB 2020) and CECT (V2019), and 1 mass was misdiagnosed. CONCLUSIONS: Bosniak classification of EFSUMB 2020 version might be as accurate as version 2019 CEUS and version 2019 CECT in diagnosing CRMs, and CEUS is found to have an excellent safety profile in dealing with clinical works.

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Purpose: We designed to construct one 3D VOI-based deep learning radiomics strategy for identifying lymph node metastases (LNM) in pancreatic ductal adenocarcinoma on the basis of multiphasic contrast-enhanced computer tomography and to assist clinical decision-making. Methods: This retrospective research enrolled 139 PDAC patients undergoing pre-operative arterial phase and venous phase scanning examination between 2015 and 2021. A primary group (training group and validation group) and an independent test group were divided. The DLR strategy included three sections. (1) Residual network three dimensional-18 (Resnet 3D-18) architecture was constructed for deep learning feature extraction. (2) Least absolute shrinkage and selection operator model was used for feature selection. (3) Fully connected network served as the classifier. The DLR strategy was applied for constructing different 3D CNN models using 5-fold cross-validation. Radiomics scores (Rad score) were calculated for distinguishing the statistical difference between negative and positive lymph nodes. A clinical model was constructed by combining significantly different clinical variables using univariate and multivariable logistic regression. The manifestation of two radiologists was detected for comparing with computer-developed models. Receiver operating characteristic curves, the area under the curve, accuracy, precision, recall, and F1 score were used for evaluating model performance. Results: A total of 45, 49, and 59 deep learning features were selected via LASSO model. No matter in which 3D CNN model, Rad score demonstrated the deep learning features were significantly different between non-LNM and LNM groups. The AP+VP DLR model yielded the best performance in predicting status of lymph node in PDAC with an AUC of 0.995 (95% CI:0.989-1.000) in training group; an AUC of 0.940 (95% CI:0.910-0.971) in validation group; and an AUC of 0.949 (95% CI:0.914-0.984) in test group. The clinical model enrolled the histological grade, CA19-9 level and CT-reported tumor size. The AP+VP DLR model outperformed AP DLR model, VP DLR model, clinical model, and two radiologists. Conclusions: The AP+VP DLR model based on Resnet 3D-18 demonstrated excellent ability for identifying LNM in PDAC, which could act as a non-invasive and accurate guide for clinical therapeutic strategies. This 3D CNN model combined with 3D tumor segmentation technology is labor-saving, promising, and effective.

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Infective endocarditis (IE), is an infection of the endocardial surfaces of the heart, which primarily affects the valve leaflets, the mural endocardium, chordae tendinae and prosthetic valves among others. IE has various complications among which neurological complications include stroke, infected intracranial aneurysms, intracranial abscesses, meningitis, encephalopathy and seizures which could prove fatal if not treated on time. We report a case of a 17 year old girl, who was a known case of bacterial endocarditis that presented with sudden onset deterioration of mental status, fever and dizziness. On CT scan imaging of the brain, the patient showed features of intracranial abscess and mycotic aneurysm. Since early detection, diagnosis and timely management is crucial for the prognosis of the patient, we should always opt for timely imaging in patients of infective endocarditis with neurological symptoms.

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Sentinel lymph node biopsy (SLNB) for staging oral squamous cell carcinoma (OSCC) patients presenting with early (T1 and T2 N0) disease in preference to elective neck dissection (END) remains controversial worldwide. A retrospective analysis of 145 patients who underwent sentinel lymph node biopsy for a previously untreated early oral cancer between 2010 and 2020 was performed. The primary outcome measures were predictors of occult metastases, accuracy of SLNB and disease specific plus overall survival. The negative predictive value, the false negative rate, and sensitivity for SLNB were 97%, 7.8%, and 92%, respectively. Depth of invasion (DOI) was a significant predictor of N status, overall survival, and disease specific survival. There was a significant difference in the incidence of the neck node metastasis in patients with DOI <5mm compared to those with DOI >5mm. For tumours >5mm there was a moderate to good correlation between radiological depth on contrast enhanced computed tomography (CECT) and histopathological DOI. Preoperative estimation of DOI may be a useful tool in the counselling of patients in the selection of either SLNB or END for N staging purposes in early OSCC.

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Purpose: This study aimed to explore the ability of texture parameters combining with machine learning methods in distinguishing intrahepatic cholangiocarcinoma (ICCA) and hepatic lymphoma (HL). Method: A total of 28 patients with HL and 101 patients with ICCA were included. A total of 45 texture features were extracted by the software LifeX from contrast-enhanced computer tomography (CECT) images and 38 of them were eligible. A total of 5 feature selection methods and 9 feature classification methods were used to build the best diagnostic models, combining with the 10-fold cross-validation to assess the accuracy of these models. The discriminative ability of each model was evaluated by receiver operating characteristic analysis. Result: A total of 45 predictive models were built by the cross combination of each selection and classification method to differentiate ICCA from HL. According to the results of test group, most of the models performed well with a large area under the curve (AUC) (>0.85) and high accuracy (>0.85). Random Forest (RF)_Linear Discriminant Analysis (LDA) (AUC = 0.997, accuracy = 0.969) was the best model among all the 45 models. Conclusion: Combining texture parameters from CECT with multiple machine learning models can differentiate ICCA and HL effectively, and RF_LDA performed the best in this process.

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Congenital intrahepatic portosystemic venous shunts are rare vascular malformations which are incidentally discovered on imaging or once hepatic encephalopathy becomes clinically apparent. Surgical ligation and endovascular embolization are potential treatments.

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Although quite rare, retroperitoneum can harbour malignant limphomas. On the grounds that the anatomical location is uncommon and the symptoms are scarce, the diagnosis is usually late and challenging. Imaging methods such as magnetic resonance imaging, computed tomography (CT) and positron emission tomography-computed tomography (PET-CT), can characterize and locate the tumor while endoscopic ultrasound fine needle aspiration (EUS-FNA) may provide pathological confirmation. We present the clinical case of a fifty-five-year-old female that is admitted to our hospital with epigastric discomfort, nausea and vomiting. CT showed a homogenously enhancing mass lesion that encased the pancreas, in contact with the portal vein, inferior vena cava, invading splenomesenteric confluence. To investigate further, EUS-FNA was decided and it revealed lymphocyte proliferation suggestive for the diagnosis of lymphoma. Hereinafter, surgical intervention was performed and immunohistochemical analysis and sub classification of lymphoma was obtained. The final diagnosis was non-Hodgkin lymphoma, Diffuse Large B-Cell Lymphoma (DLBCL). Poly-chemotherapy with R-CHOP was initiated. At the end of the treatment fluorodeoxyglucose positron emission tomography (FDG-PET) was performed and no pathological findings were found. A brief review of literature is also provided.

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Extramedullary hematopoiesis (EMH) is hematopoiesis in organs outside the bone marrow and most frequently occurs in the liver, spleen, and lymph nodes. We report a case of perirenal EMH revealed by kidney biopsy in a patient with primary myelofibrosis. We observed only bilateral kidney enlargement with plain computed tomography (CT) and ultrasonography before obtaining a renal biopsy. We obtained a percutaneous biopsy from the lower pole of the left kidney using ultrasonographic guidance. Ultrasonography just after the renal biopsy revealed no bleeding around the kidney. However, early the next morning, the patient developed severe hemorrhagic shock. Contrast-enhanced CT at that time revealed a massive hematoma in the left posterior perirenal space and bilateral abnormalities of the perirenal soft tissues. In patients with primary myelofibrosis, if plain CT shows an abnormal renal enlargement, EMH should be considered. In addition, a contrast-enhanced CT should be obtained before performing a percutaneous renal biopsy to assess for the possibility of perirenal EMH in these patients.

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INTRODUCTION: Several study supported that 18F-Fluoro-deoxy-glucose (FDG) positron emission tomography/computer tomography with low dose CT (standard PET/CT) is more accurate than contrast-enhanced CT (ceCT) in the primary staging of Hodgkin disease. AIM: The authors compared the accuracy of these examinations with this indication in their practice, and analysed the added value of ceCT which was performed as a supplement to standard PET/CT. METHOD: Twenty-eight patients were categorized based on ceCT, single standard PET/CT and standard PET/CT with ceCT. RESULTS: Twenty-four patients were in the same disease-stage based on all methods. Disease was upstaged by standard PET/CT compared to ceCT in 4 patients. There was no change in stage when comparing standard PET/CT and standard PET/CT with ceCT. CONCLUSIONS: Standard PET/CT is more accurate than ceCT in the primary staging of Hodgkin disease. The authors established that it is not reasonable to supplement standard PET/CT with ceCT in this indication.

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Objective To evaluate the diagnostic value of ultrasonography (USG) and contrast-enhanced computer tomography (CT) for thyroid carcinoma.MethodsThe results of the review of the preoperative CT and those of the original US reports were compared with the histopathologic results in 73 cases of thyroid carcinoma who underwent radical operation and central compartment dissection from November 2009 to November 2011.ResultsThe final diagnostic rate of thyroid carcinoma with USG was 69.9％,CT of that was 80.8％.There were no significant difference between them (P =0.077).The diagnostic rate of metastatic lymph node in the central compartment with USG was 61.6％,positive predictive value was 64.0％,negative predictive value was 60.4％.The diagnostic rate of metastatic lymph node in the central compartment with CT was 67.1％,positive predictive value was 61.7％,negative predictive value was 76.9％.There were not significant difference between them(P =0.848,P =0.152,P =0.489).Conclusion There was no significant difference between USG and CT in The final diagnostic rate of thyroid carcinoma and its lymph node metastasis in the central compartment.