Incidence, Presentation, and Natural History of Adrenal Hemorrhage: An Institutional Analysis.

INTRODUCTION: Adrenal hemorrhage (AH) can occur due to multiple etiologies with variable radiographic appearance, often indistinguishable from underlying adrenal neoplasms. There is a lack of AH literature and evidence-based guidelines. Our study aimed to understand the prevalence and etiology of AH, follow-up, and incidence of underlying neoplasm. METHODS: An institutional database was queried from January 2006 to October 2021 for patients with AH on imaging, excluding patients with known malignancies, adrenal masses, or prior adrenal surgery. Demographics, medical history, hematoma size, laterality, biochemical evaluation, intervention, and additional imaging were reviewed. RESULTS: Of 490,301 imaging reports queried, 530 (0.11%) with AH met inclusion criteria. Most imaging (n = 485, 91.5%) was performed during trauma evaluation. Two patients underwent dedicated intervention at presentation. Interval imaging was performed in 114 (21.5%) patients at a median of 2.6 (interquartile range 0.99-13.4) mo, with resolution (n = 84, 73.7%) or decreased size of AH (n = 21, 18.4%) in most patients. Only 10 patients (1.9%) saw an outpatient provider in our system to address AH or evaluate for underlying mass, and 9 (1.7%) underwent biochemical screening. Thirteen patients (11% of 118 patients with any follow-up) had evidence of an adrenal mass, confirmed on serial imaging (n = 10) or adrenalectomy (n = 3). Scans performed for nontrauma indications were significantly more likely to have an underlying mass (n = 6/26 [23.1%]) than those performed for trauma evaluation (n = 7/92 [7.6%], P = 0.04). CONCLUSIONS: AH is a rare finding associated with an increased rate of underlying adrenal mass, particularly when unrelated to trauma. Most AH resolves spontaneously without intervention. Follow-up imaging at 6 mo can help distinguish mass-associated AH from simple hemorrhage.

Advances in Deep Neuropathological Phenotyping of Alzheimer Disease: Past, Present, and Future.

Alzheimer disease (AD) is a neurodegenerative disorder characterized pathologically by the presence of neurofibrillary tangles and amyloid beta (Aß) plaques in the brain. The disease was first described in 1906 by Alois Alzheimer, and since then, there have been many advancements in technologies that have aided in unlocking the secrets of this devastating disease. Such advancements include improving microscopy and staining techniques, refining diagnostic criteria for the disease, and increased appreciation for disease heterogeneity both in neuroanatomic location of abnormalities as well as overlap with other brain diseases; for example, Lewy body disease and vascular dementia. Despite numerous advancements, there is still much to achieve as there is not a cure for AD and postmortem histological analyses is still the gold standard for appreciating AD neuropathologic changes. Recent technological advances such as in-vivo biomarkers and machine learning algorithms permit great strides in disease understanding, and pave the way for potential new therapies and precision medicine approaches. Here, we review the history of human AD neuropathology research to include the notable advancements in understanding common co-pathologies in the setting of AD, and microscopy and staining methods. We also discuss future approaches with a specific focus on deep phenotyping using machine learning.