Case 304: Porphyria Cutanea Tarda.

HISTORY: In 2017, a 72-year-old woman was seen in the gastroenterology department with a 2-month history of mild and intermittent abdominal pain without other accompanying symptoms. Her medical history was unremarkable, except for a previous visit due to facial photodermatitis 3 years earlier. Diazepam for a sleeping disorder was the only chronic medication recorded. Results of physical examination, blood count, and basic metabolic panels including assessment of renal and liver function were normal; only the ferritin level was slightly elevated (265 ng/mL [595 pmol/L]; normal range, 10-120 ng/mL [22-269 pmol/L]). Abdominal US was performed, followed by multiphasic contrast-enhanced CT and liver MRI due to the findings of the first study. A diagnosis was not established in that moment, and acetaminophen was prescribed for pain relief. As the symptoms continued, laboratory tests and imaging studies were repeated 2 years later, with similar findings and no notable changes.

Case 304.

History In 2017, a 72-year-old woman was seen in the gastroenterology department with a 2-month history of mild and intermittent abdominal pain without other accompanying symptoms. Her medical history was unremarkable, except for a previous visit due to facial photodermatitis 3 years earlier. Diazepam for a sleeping disorder was the only chronic medication recorded. Results of physical examination, blood count, and basic metabolic panels including assessment of renal and liver function were normal; only the ferritin level was slightly elevated (265 ng/mL [595 pmol/L]; normal range, 10-120 ng/mL [22-269 pmol/L]). Abdominal US was performed, followed by multiphasic contrast-enhanced CT and liver MRI due to the findings of the first study. A diagnosis was not established in that moment, and acetaminophen was prescribed for pain relief. As the symptoms continued, laboratory tests and imaging studies were repeated 2 years later, with similar findings and no notable changes (Figs 1-5).

Meningioma Consistency Can Be Defined by Combining the Radiomic Features of Magnetic Resonance Imaging and Ultrasound Elastography. A Pilot Study Using Machine Learning Classifiers.

BACKGROUND: The consistency of meningioma is a factor that may influence surgical planning and the extent of resection. The aim of our study is to develop a predictive model of tumor consistency using the radiomic features of preoperative magnetic resonance imaging and the tumor elasticity measured by intraoperative ultrasound elastography (IOUS-E) as a reference parameter. METHODS: A retrospective analysis was performed on supratentorial meningiomas that were operated on between March 2018 and July 2020. Cases with IOUS-E studies were included. A semiquantitative analysis of elastograms was used to define the meningioma consistency. MRIs were preprocessed before extracting radiomic features. Predictive models were built using a combination of feature selection filters and machine learning algorithms: logistic regression, Naive Bayes, k-nearest neighbors, Random Forest, Support Vector Machine, and Neural Network. A stratified 5-fold cross-validation was performed. Then, models were evaluated using the area under the curve and classification accuracy. RESULTS: Eighteen patients were available for analysis. Meningiomas were classified as hard or soft according to a mean tissue elasticity threshold of 120. The best-ranked radiomic features were obtained from T1-weighted post-contrast, apparent diffusion coefficient map, and T2-weighted images. The combination of Information Gain and ReliefF filters with the Naive Bayes algorithm resulted in an area under the curve of 0.961 and classification accuracy of 94%. CONCLUSIONS: We have developed a high-precision classification model that is capable of predicting consistency of meningiomas based on the radiomic features in preoperative magnetic resonance imaging (T2-weighted, T1-weighted post-contrast, and apparent diffusion coefficient map).

Type V biliary cyst with cystolithiasis.

We present the case of a 40-year-old female who presented to the General Surgery clinic due to a single episode of abdominal pain which required a visit to the Emergency Department. The patient had undergone surgery during childhood due to the suspicion of a hepatic hydatid cyst. However, an intraoperative cholangiography identified a small, non-complicated biliary cyst. Therefore, a hepatic resection was not performed. The patient did not undergo follow-up of the lesion.

Review of imaging techniques in the diagnosis of hepatocellular carcinoma in patients who require a liver transplant.

OBJECTIVES: The aim of the study was to retrospectively compare the diagnostic performance of ultrasound (US), contrast-enhanced multidetector computed tomography (MDCT) and contrast-enhanced MRI in cirrhotic patients who were candidates for liver transplantation. MATERIALS AND METHODS: A total of 273 consecutive patients with 218 hepatocellular carcinoma (HCC) nodules, who underwent imaging and subsequent transplantation, were examined. Diagnosis of HCC was based on explant correlation of the whole liver. Three different imaging data sets were evaluated: US, MDCT and MRI unenhanced and dynamic phases. Diagnostic accuracy, sensitivity, specificity, positive predictive value and negative predictive value, with corresponding 95% confidence intervals, were determined. Statistical analysis was performed for all lesions and for two lesion subgroups (≤2 and >2 cm). Preoperative tumour staging was analysed. RESULTS: Patient sensitivity to US, MDCT and MRI was 80.4, 81.1 and 90.5%, respectively. Specificity was 96.3, 96.2 and 82.1%. Combined US and MDCT improved sensitivity (88%) without significant loss in specificity (95.7%). Imaging tests resulted in accurate tumour staging in 83.4% of the patients. In per-nodule analysis, technique sensitivity was 55.6, 52.4 and 65.9%, respectively. Sensitivity figures improved when the nodule was larger than 2 cm. CONCLUSION: Combining imaging techniques is a good strategy for pretransplant HCC diagnosis and provides more accurate cancer staging in patients, which is necessary to decide the correct therapeutic approach.