Risk factors associated with microembolization after carotid intervention.

BACKGROUND: Microembolization after carotid artery stenting (CAS) and carotid endarterectomy (CEA) has been documented and may confer risk for neurocognitive impairment. Patients undergoing stenting are known to be at higher risk for microembolization. In this prospective cohort study, we compare the microembolization rates for patients undergoing CAS and CEA and perioperative characteristics that may be associated with microembolization. METHODS: Patients undergoing CAS and CEA were prospectively recruited under local institutional review board approval from an academic medical center. All patients also received 3T brain magnetic resonance imaging with a diffusion-weighted imaging sequence preoperatively and within 24 hours postoperatively to identify procedure-related new embolic lesions. Preoperative, postoperative, procedural factors, and plaque characteristics were collected. Factors were tested for statistical significance with logistic regression. RESULTS: A total of 202 patients were enrolled in the study. There were 107 patients who underwent CAS and 95 underwent CEA. Patients undergoing CAS were more likely to have microemboli than patients undergoing CEA (78% vs 27%; P < .0001). For patients undergoing CAS, patency of the external carotid artery (odds ratio [OR], 11.4; 95% confidence interval [CI], 1.11-117.6; P = .04), lesion calcification (OR, 5.68; 95% CI, 1.12-28.79; P = .04), and lesion length (OR, 0.29; 95% CI, 0.08-1.01; P = .05) were all found to be independent risk factors for perioperative embolization. These factors did not confer increased risk to patients undergoing CEA. CONCLUSIONS: Patients undergoing CAS are at higher risk for perioperative embolization. The risk for perioperative embolization is related to the length of the lesion and calcification. Identifying the preoperative risk factors may help to guide patient selection and, thereby, reduce embolization-related neurocognitive impairment.

Investigating Tau and Amyloid Tracer Skull Binding in Studies of Alzheimer Disease.

Off-target binding of [18F]flortaucipir (FTP) can complicate quantitative PET analyses. An underdiscussed off-target region is the skull. Here, we characterize how often FTP skull binding occurs, its influence on estimates of Alzheimer disease pathology, its potential drivers, and whether skull uptake is a stable feature across time and tracers. Methods: In 313 cognitively normal and mildly impaired participants, CT scans were used to define a skull mask. This mask was used to quantify FTP skull uptake. Skull uptake of the amyloid-ß PET tracers [18F]florbetapir and [11C]Pittsburgh compound B (n = 152) was also assessed. Gaussian mixture modeling defined abnormal levels of skull binding for each tracer. We examined the relationship of continuous bone uptake to known off-target binding in the basal ganglia and choroid plexus as well as skull density measured from the CT. Finally, we examined the confounding effect of skull binding on pathologic quantification. Results: We found that 50 of 313 (∼16%) FTP scans had high levels of skull signal. Most were female (n = 41, 82%), and in women, lower skull density was related to higher FTP skull signal. Visual reads by a neuroradiologist revealed a significant relationship with hyperostosis; however, only 21% of women with high skull binding were diagnosed with hyperostosis. FTP skull signal did not substantially correlate with other known off-target regions. Skull uptake was consistent over longitudinal FTP scans and across tracers. In amyloid-ß-negative, but not -positive, individuals, FTP skull binding impacted quantitative estimates in temporal regions. Conclusion: FTP skull binding is a stable, participant-specific phenomenon and is unrelated to known off-target regions. Effects were found primarily in women and were partially related to lower bone density. The presence of [11C]Pittsburgh compound B skull binding suggests that defluorination does not fully explain FTP skull signal. As signal in skull bone can impact quantitative analyses and differs across sex, it should be explicitly addressed in studies of aging and Alzheimer disease.

The Brain Tumor Segmentation (BraTS-METS) Challenge 2023: Brain Metastasis Segmentation on Pre-treatment MRI.

Clinical monitoring of metastatic disease to the brain can be a laborious and timeconsuming process, especially in cases involving multiple metastases when the assessment is performed manually. The Response Assessment in Neuro-Oncology Brain Metastases (RANO-BM) guideline, which utilizes the unidimensional longest diameter, is commonly used in clinical and research settings to evaluate response to therapy in patients with brain metastases. However, accurate volumetric assessment of the lesion and surrounding peri-lesional edema holds significant importance in clinical decision-making and can greatly enhance outcome prediction. The unique challenge in performing segmentations of brain metastases lies in their common occurrence as small lesions. Detection and segmentation of lesions that are smaller than 10 mm in size has not demonstrated high accuracy in prior publications. The brain metastases challenge sets itself apart from previously conducted MICCAI challenges on glioma segmentation due to the significant variability in lesion size. Unlike gliomas, which tend to be larger on presentation scans, brain metastases exhibit a wide range of sizes and tend to include small lesions. We hope that the BraTS-METS dataset and challenge will advance the field of automated brain metastasis detection and segmentation.