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Objective: We aimed to investigate the distribution of [68Ga]Ga-p14-032, a novel PET ligand that binds to vascular amyloid, in patients diagnosed clinically with probable cerebral amyloid angiopathy (CAA) compared with patients with Alzheimer's disease (AD) and normal controls (NC).Methods: This longitudinal cohort study was composed of 10 subjects (three probable CAA patients, two AD patients, five NC subjects), recruited from a clinic in China. CAA patients had a history of lobar intracerebral hemorrhage (ICH) and met modified Boston criteria for probable CAA. All participants were aged at least 55 years and underwent [68Ga] Ga-p14-032 PET/CT or/and PET/MRI, and the Montreal Cognitive Assessment on initial assessment. Demographics were measured at baseline (diabetes, hypertension, hypercholesterolemia, ischemic stroke, and ICH). Two PET imaging experts reviewed the PET images with cortical standardized uptake value ratio (SUVr) displayed on a color scale and visually classified the images as positive or negative. The mean of SUVr was calculated using the pons as reference.Results: In CAA patients, PET scans were positive in regions with higher numbers of CMBs. No significant signal was seen in AD subjects or controls. The relative [68Ga]Ga-p14-032 retention in the cortex was stronger in patients with CAA than AD and NC (median SUVr 2.68 ± 1.53 vs. 1.77 ± 0.08 and 0.83 ± 0.24).Conclusions: Our results provide early evidence that the [68Ga] Ga-p14-032 PET probe binds preferentially to vascular amyloid and may be a useful tracer for diagnosing CAA.

Background: Patients with poor-grade aneurysmal subarachnoid hemorrhage (aSAH), defined as World Federation of Neurosurgical Societies (WFNS) grades IV–V have high rates of disability and mortality. The objective of this study was to accurately prognosticate the outcomes of patients with poor-grade aSAH by developing a new scoring model.Methods: A total of 147 poor-grade aSAH patients in our center were enrolled. Risk variables identified by multivariate logistic regression analysis were used to devise a scoring model (total score, 0–9 points). The scores were estimated on the basis of β coefficients. A cohort of 68 patients from another institute was used to validate the model.Results: Multivariate logistic regression analysis revealed that modified Fisher grade >2 [odds ratio [OR], 2.972; P = 0.034], age ≥65 years (OR, 3.534; P = 0.006), conservative treatment (OR, 5.078; P = 0.019), WFNS grade V (OR, 2.638; P = 0.029), delayed cerebral ischemia (OR, 3.170; P = 0.016), shunt-dependent hydrocephalus (OR, 3.202; P = 0.032), and cerebral herniation (OR, 7.337; P < 0.001) were significant predictors for poor prognosis [modified Rankin Scale [mRS] ≥3]. A scoring system was constructed by the integration of these factors and divided the poor-grade aSAH patients into three categories: low risk (0–1 points), intermediate risk (2–3 points), and high risk (4–9 points), with predicted risks of poor prognosis of 11, 52, and 87%, respectively (P < 0.001). The area under the curve in the derivation cohort was 0.844 (95% CI, 0.778–0.909). The AUC in the validation cohort was 0.831 (95% CI, 0.732–0.929).Conclusions: The new scoring model can improve prognostication and help decision-making for subsequent complementary treatment in patients with aSAH.