Zeitschrift für entzündliche Darmerkrankungen und -störungen

Aortic angiosarcoma is a rare and aggressive form of cancer originating from the endothelial cells of the aorta. Due to its rarity and nonspecific
symptoms, it often presents diagnostic challenges and is typically diagnosed at an advanced stage. This case report discusses a unique
presentation of aortic angiosarcoma manifesting primarily as musculoskeletal metastases, emphasizing the diagnostic process, clinical features,
and therapeutic considerations. A 62-year-old male with no significant past medical history presented to the orthopedic clinic with complaints
of persistent pain and swelling in his left thigh and right shoulder. The symptoms had been progressively worsening over the past six months,
significantly impairing his daily activities. There was no history of trauma or significant weight loss, and initial clinical examination suggested a
musculoskeletal origin.

but significant manifestation is obstructive jaundice. Obstructive jaundice occurs when there is a blockage in the bile ducts, which hinders the
normal flow of bile from the liver to the intestines. This blockage leads to a buildup of bilirubin in the blood, resulting in yellowing of the skin and
eyes (jaundice). The intersection of lung cancer and obstructive jaundice presents a challenging diagnostic and therapeutic scenario, requiring a
multidisciplinary approach for effective management.
Lung cancer, particularly small cell lung cancer and non-small cell lung cancer, can metastasize to various organs, including the liver. The primary
mechanisms by which lung cancer can lead to obstructive jaundice. Lung cancer can metastasize to the liver, causing direct obstruction of the
intrahepatic bile ducts. This leads to jaundice as the bile flow is impeded within the liver.

Ulcerative Colitis (UC) is a Chronic Inflammatory Bowel Disease (IBD) characterized by inflammation of the colon and rectum. The diagnosis and
treatment of UC can be complex due to its unpredictable nature, which can vary widely in severity and response to treatment. Traditional diagnostic
methods, such as endoscopy and biopsy, are invasive and often associated with discomfort for the patient. Moreover, treatment strategies can
involve a trial-and-error approach, given the variability in individual responses to medications. In recent years, the advent of Artificial Intelligence
(AI) has shown promise in transforming the landscape of UC management. AI technologies, including Machine Learning (ML) and Deep Learning
(DL), are increasingly being utilized to enhance diagnostic accuracy, personalize treatment plans, and predict disease course, thereby improving
patient outcomes and reducing healthcare costs. AI's role in UC diagnosis primarily revolves around enhancing the capabilities of imaging and
endoscopy. Traditional endoscopic procedures involve visual assessment by a gastroenterologist to identify inflammation, ulcers, and other
abnormalities. AI algorithms, particularly those based on DL, have been developed to assist in the interpretation of endoscopic images. These
algorithms can detect subtle mucosal changes that may be indicative of UC with higher accuracy and consistency compared to human observers.

Celiac Disease (CD) is a chronic autoimmune disorder primarily affecting the small intestine, triggered by the ingestion of gluten in genetically
predisposed individuals. It is characterized by a wide range of clinical manifestations, from gastrointestinal symptoms to extra-intestinal symptoms
such as anemia, osteoporosis, and neurological issues. The only effective treatment for CD is a strict, lifelong Gluten-free diet. However, monitoring
adherence to this diet and assessing disease activity present significant challenges. An international method for monitoring celiac disease involves
standardized approaches to diagnosis, follow-up, and management, incorporating serological, histological, and clinical evaluations.
The diagnosis of CD typically involves a combination of serological tests, genetic testing, and intestinal biopsy. The most common serological
markers include anti-tissue Trans Glutaminase (tTG) antibodies and anti-endo mysial antibodies. The presence of these antibodies suggests
an autoimmune response to gluten. Genetic testing can identify the presence of HLA-DQ2 or HLA-DQ8 haplotypes, which are necessary but
not sufficient for the development of CD. A definitive diagnosis often requires a biopsy of the small intestine to confirm villous atrophy and crypt
hyperplasia.