Abdominal metastases from Merkel cell carcinoma: Prevalence and presentation on CT examination in 111 patients

CT and MRI of abdominal cancers: current trends and perspectives in the era of radiomics and artificial intelligence

Abdominal cancers continue to pose daily challenges to clinicians, radiologists and researchers. These challenges are faced at each stage of abdominal cancer management, including early detection, accurate characterization, precise assessment of tumor spread, preoperative planning when surgery is anticipated, prediction of tumor aggressiveness, response to therapy, and detection of recurrence. Technical advances in medical imaging, often in combination with imaging biomarkers, show great promise in addressing such challenges. Information extracted from imaging datasets owing to the application of radiomics can be used to further improve the diagnostic capabilities of imaging. However, the analysis of the huge amount of data provided by these advances is a difficult task in daily practice. Artificial intelligence has the potential to help radiologists in all these challenges. Notably, the applications of AI in the field of abdominal cancers are expanding and now include diverse approaches for cancer detection, diagnosis and classification, genomics and detection of genetic alterations, analysis of tumor microenvironment, identification of predictive biomarkers and follow-up. However, AI currently has some limitations that need further refinement for implementation in the clinical setting. This review article sums up recent advances in imaging of abdominal cancers in the field of image/data acquisition, tumor detection, tumor characterization, prognosis, and treatment response evaluation.

Three-dimensional CT cinematic rendering of adrenal masses: Role in tumor analysis and management

The adrenal gland is home to an array of complex physiological and neoplastic disease processes. While dedicated adrenal computed tomography (CT) is the gold standard imaging modality for adrenal lesions, there exists significant overlap among imaging features of adrenal pathology. This can often make radiological diagnosis and subsequent determination of the optimal surgical approach challenging. Cinematic rendering (CR) is a novel CT post-processing technique that utilizes advanced light modeling to generate highly photorealistic anatomic visualization. This generates unique prospects in the evaluation of adrenal masses. As one of the first large tertiary care centers to incorporate CR into routine diagnostic workup, our preliminary experience with using CR has been positive, and we have found CR to be a valuable adjunct during surgical planning. Herein, we highlight the unique utility of CR techniques in the workup of adrenal lesions and provide commentary on the opportunities and obstacles associated with the application of this novel display method in this setting.

Large Intestinal Obstruction and Perforation From Metastatic Merkel Cell Carcinoma: A Case Report

Merkel cell carcinoma (MCC) is a rare and aggressive neuroendocrine neoplasm of the skin that has a high propensity to metastasize. Abdominal metastases of MCC have been described previously though these are typically regional with nodal spread. We report the case of a 60-year-old man with a history of left upper extremity MCC who had resection, radiation therapy, and immunotherapy. He ultimately developed large bowel obstruction from metastatic intraperitoneal implants. A 6 cm mass at the descending colon was biopsied and proven to be metastatic MCC. The tumor eroded through the wall of the colon and perforated, requiring emergent colectomy for septic shock. Herein, we describe the first case of colonic perforation secondary to metastatic MCC. This case illustrates the importance of expedient and multifactorial management of patients with rapidly growing metastatic colonic tumors that are at risk for perforation.

An Extraordinary Cause of Colonic Obstruction: Merkel Cell Carcinoma of Unknown Primary

Merkel cell carcinoma is an aggressive and rare neuroendocrine skin cancer with documented metastases to the liver, lungs, and, seldom, the gastrointestinal tract. Metastases to the colon are rare but are seen with primary skin lesions or recurrent disease. Presented is a patient with large bowel obstruction secondary to a large hepatic flexure mass. Pathologic workup revealed Merkel cell carcinoma, and a dermatologic evaluation did not identify a primary cutaneous lesion. This is the first reported case of Merkel cell carcinoma of unknown primary presenting as large bowel obstruction.

Artificial intelligence in adrenal imaging: A critical review of current applications

In the elective field of adrenal imaging, artificial intelligence (AI) can be used for adrenal lesion detection, characterization, hypersecreting syndrome management and patient follow-up. Although a perfect AI tool that includes all required steps from detection to analysis does not exist yet, multiple AI algorithms have been developed and tested with encouraging results. However, AI in this setting is still at an early stage. In this regard, most published studies about AI in adrenal gland imaging report preliminary results that do not have yet daily applications in clinical practice. In this review, recent developments and current results of AI in the field of adrenal imaging are presented. Limitations and future perspectives of AI are discussed.

Imaging of Pancreatic Ductal Adenocarcinoma: An Update on Recent Advances

Pancreatic ductal carcinoma (PDAC) is one of the leading causes of cancer-related death worldwide. Computed tomography (CT) remains the primary imaging modality for diagnosis of PDAC. However, CT has limitations for early pancreatic tumor detection and tumor characterization so that it is currently challenged by magnetic resonance imaging. More recently, a particular attention has been given to radiomics for the characterization of pancreatic lesions using extraction and analysis of quantitative imaging features. In addition, radiomics has currently many applications that are developed in conjunction with artificial intelligence (AI) with the aim of better characterizing pancreatic lesions and providing a more precise assessment of tumor burden. This review article sums up recent advances in imaging of PDAC in the field of image/data acquisition, tumor detection, tumor characterization, treatment response evaluation, and preoperative planning. In addition, current applications of radiomics and AI in the field of PDAC are discussed.