The superior cerebellar artery (SCA) arises from the distal part of the basilar artery and passes by the oculomotor, trochlear, and trigeminal nerves. SCA is known to play a crucial role in the development of trigeminal neuralgia. However, due to its anatomical variability, it may also trigger other neurovascular compression (NVC), including hemifacial spasm, oculomotor nerve palsy, and ocular neuromyotonia. Additionally, it may be associated with ischemic syndromes and aneurysm development, highlighting its clinical significance. The most common anatomical variations of the SCA include duplication, a single vessel origin from the posterior cerebral artery (PCA), and a common trunk with PCA. Rarely observed variants include bifurcation and origin from the internal carotid artery. Certain anatomical variants such as early bifurcation and caudal course of duplicated SCA trunk may increase the risk of NVC. In this narrative review, we aimed to examine the impact of the anatomical variations of SCA on the NVCs based on papers published in Pubmed, Scopus, and Web of Science databases with a snowballing approach. Our review emphasizes the importance of a thorough understanding of the anatomical variability of SCA to optimize the management of patients with NVCs associated with this artery.

The anterior inferior cerebellar artery (AICA) is situated within the posterior cranial fossa and typically arises from the basilar artery, usually at the pontomedullary junction. AICA is implicated in various clinical conditions, encompassing the development of aneurysms, thrombus formation, and the manifestation of lateral pontine syndrome. Furthermore, owing to its close proximity to cranial nerves within the middle cerebellopontine angle, AICA’s pulsatile compression at the root entry/exit zone of cranial nerves may give rise to specific neurovascular compression syndromes (NVCs), including hemifacial spasm (HFS) and geniculate neuralgia concurrent with HFS. In this narrative review, we undertake an examination of the influence of anatomical variations in AICA on the occurrence of NVCs. Significant methodological disparities between cadaveric and radiological studies (CTA, MRA, and DSA) were found, particularly in diagnosing AICA’s absence, which was more common in radiological studies (up to 36.1%) compared to cadaver studies (less than 5%). Other observed variations included atypical origins from the vertebral artery and basilar-vertebral junction, as well as the AICA-and-PICA common trunk. Single cases of arterial triplication or fenestration have also been documented. Specifically, in relation to HFS, AICA variants that compress the facial nerve at its root entry/exit zone include parabola-shaped loops, dominant segments proximal to the REZ, and anchor-shaped bifurcations impacting the nerve’s cisternal portion.

Pancreatic cancer is one of the most lethal neoplasms. Despite considerable research conducted in recent decades, not much has been achieved to improve its survival rate. That may stem from the lack of effective screening strategies in increased pancreatic cancer risk groups. One population that may be appropriate for screening is new-onset diabetes (NOD) patients. Such a conclusion stems from the fact that pancreatic cancer can cause diabetes several months before diagnosis. The most widely used screening tool for this population, the ENDPAC (Enriching New-Onset Diabetes for Pancreatic Cancer) model, has not achieved satisfactory results in validation trials. This provoked the first attempts at using artificial intelligence (AI) to create larger, multi-parameter models that could better identify the at-risk population, which would be suitable for screening. The results shown by the authors of these trials seem promising. Nonetheless, the number of publications is limited, and the downfalls of using AI are not well highlighted. This narrative review presents a summary of previous publications, recent advancements and feasible solutions for effective screening of patients with NOD for pancreatic cancer.