Stroke, including ischemic stroke and hemorrhagic stroke, is a high prevalence and life-threatening cerebrovascular condition. Intracranial aneurysms stand as a common cause of hemorrhagic strokes, whereas intracranial artery stenosis caused by atherosclerosis emerges as the predominant cause of ischemic strokes. Accurate assessment of intracranial aneurysm and intracranial artery stenosis is important for the diagnosis and treatment of cerebrovascular diseases. Magnetic resonance angiography (MRA) is widely used to visualize the cerebral arterial tree for disease diagnosis, especially for the screening of intracranial atherosclerosis and aneurysm. Accurate lesion detection and segmentation are important for quantitative analysis of cerebrovascular diseases, such as estimation of degree of luminal stenosis and the size of aneurysm. However, manual detection and segmentation of MRA can be challenging even for experts given the complex network of cerebral arteries with substantial inter-individual variations, and weak signals in small vessels due to slow or in-plane blood flow. Time-of-flight (TOF) MRA is the most widely used non-invasive imaging technique to depict the anatomy of the cerebrovascular tree without use of contrast agents. Due to its non-invasive nature and absence of ionizing radiation, TOF-MRA imposes minimal harm on the human body, making it suitable for clinical screening of cerebrovascular diseases. Private datasets and annotations are commonly used in recent cerebral artery segmentation studies, whereas open-accessible large-scale TOF-MRA data with well-labeled bounding boxes and segmentation masks of intracranial aneurysm and intracranial artery stenosis are rare, hindering the development and validation of reliable automatic intracranial lesion detection and segmentation algorithms. Hence, we attempt to host the first intracranial aneurysm and intracranial artery stenosis detection and segmentation challenge in MICCAI 2024. To the best of our knowledge, this is the first intracranial lesion detection and segmentation challenge based on TOF-MRA data. In this challenge, the task is to detect and segment lesion from 3D TOF-MRA images acquired from a cohort consisting of healthy volunteers and patients with intracranial artery stenosis or intracranial aneurysms. Precise detection and segmentation of lesions will be helpful for the identification and quantitative characterization of stenosis and intracranial aneurysm, which is important in clinical practice. Notably, this challenge is also the official grand challenge of 2024 Annual meeting of Society for Magnetic Resonance Angiography (SMRA, https://society4mra.org/), which was founded in 1989 as the MR Angio Club to bring together scientists, clinicians and industry with a common interest in MR Angiography (MRA). As an MRA imaging academic society, SMRA was holding challenges since 2021, and all of them were also joint MICCAI challenge.