Background and Purpose: We explored whether high-degree magnetic resonance imaging–visible perivascular spaces in centrum semiovale (CSO) are more prevalent in cerebral amyloid angiopathy (CAA) than hypertensive small vessel disease and their relationship to brain amyloid retention in patients with primary intracerebral hemorrhage (ICH). Methods: One hundred and eight spontaneous ICH patients who underwent magnetic resonance imaging and Pittsburgh compound B were enrolled. Topography and severity of enlarged perivascular spaces were compared between CAA-related ICH (CAA-ICH) and hypertensive small vessel disease–related ICH (non-CAA ICH). Clinical and image characteristics associated with high-degree perivascular spaces were evaluated in univariate and multivariable analyses. Univariate and multivariable models were performed to evaluate associations between the severity of perivascular spaces in CSO and amyloid retention in CAA-ICH and non–CAA-ICH cases. Results: Patients with CAA-ICH (n=29) and non–CAA-ICH (n=79) had similar prevalence of high-degree perivascular spaces in CSO (44.8% versus 36.7%; P =0.507) and in basal ganglia (34.5% versus 51.9%; P =0.131). High-degree perivascular spaces in CSO were independently associated with the presence of lobar microbleed (odds ratio, 3.0 [95% CI, 1.1–8.0]; P =0.032). The amyloid retention was higher in those with high-degree than those with low-degree CSO-perivascular spaces in CAA-ICH (global Pittsburgh compound B standardized uptake value ratio, 1.55 [1.33–1.61] versus 1.13 [1.01–1.48]; P =0.003) but not in non–CAA-ICH. In CAA-ICH, the association between cerebral amyloid retention and the degree of perivascular spaces in CSO remained significant after adjustment for age and lobar microbleed number ( P =0.004). Conclusions: Although high-degree magnetic resonance imaging–visible perivascular spaces are equally prevalent between CAA-ICH and non–CAA-ICH in the Asian cohort, the severity of magnetic resonance imaging–visible CSO-perivascular spaces may be an indicator of higher brain amyloid deposition in patients with CAA-ICH.

Participation in enjoyable activities is essential for the health and development of young children with and without disabilities. For preschool children with autism spectrum disorder (ASD), there is limited knowledge regarding their participation in play, learning, recreation, and social activities. This was a preliminary study that compares the participation between children 2–6 years of age with ASD (n = 25) and age- and sex-matched typically developing (TD) (n = 25) children. The Chinese version of the Assessment of Preschool Children’s Participation (APCP-C) measures participation in play, skill development, active physical recreation, and social activities. Parents of the children in this study completed the APCP-C by structured interview. The results showed that children with ASD had lower participation diversity and intensity than TD children in play activities. A lower percentage of children participating in individual activity was found for children with ASD than TD children in most APCP-C activities. Professionals that serve young children with special needs are encouraged to partner with parents to provide playful and socially enhancing activities for preschool children with ASD.

BackgroundThe Skeletal Oncology Research Group machine-learning algorithm (SORG-MLA) was developed to predict the survival of patients with spinal metastasis. The algorithm was successfully tested in five international institutions using 1101 patients from different continents. The incorporation of 18 prognostic factors strengthens its predictive ability but limits its clinical utility because some prognostic factors might not be clinically available when a clinician wishes to make a prediction.Questions/purposesWe performed this study to (1) evaluate the SORG-MLA’s performance with data and (2) develop an internet-based application to impute the missing data.MethodsA total of 2768 patients were included in this study. The data of 617 patients who were treated surgically were intentionally erased, and the data of the other 2151 patients who were treated with radiotherapy and medical treatment were used to impute the artificially missing data. Compared with those who were treated nonsurgically, patients undergoing surgery were younger (median 59 years [IQR 51 to 67 years] versus median 62 years [IQR 53 to 71 years]) and had a higher proportion of patients with at least three spinal metastatic levels (77% [474 of 617] versus 72% [1547 of 2151]), more neurologic deficit (normal American Spinal Injury Association [E] 68% [301 of 443] versus 79% [1227 of 1561]), higher BMI (23 kg/m2 [IQR 20 to 25 kg/m2] versus 22 kg/m2 [IQR 20 to 25 kg/m2]), higher platelet count (240 × 103/µL [IQR 173 to 327 × 103/µL] versus 227 × 103/µL [IQR 165 to 302 × 103/µL], higher lymphocyte count (15 × 103/µL [IQR 9 to 21× 103/µL] versus 14 × 103/µL [IQR 8 to 21 × 103/µL]), lower serum creatinine level (0.7 mg/dL [IQR 0.6 to 0.9 mg/dL] versus 0.8 mg/dL [IQR 0.6 to 1.0 mg/dL]), less previous systemic therapy (19% [115 of 617] versus 24% [526 of 2151]), fewer Charlson comorbidities other than cancer (28% [170 of 617] versus 36% [770 of 2151]), and longer median survival. The two patient groups did not differ in other regards. These findings aligned with our institutional philosophy of selecting patients for surgical intervention based on their level of favorable prognostic factors such as BMI or lymphocyte counts and lower levels of unfavorable prognostic factors such as white blood cell counts or serum creatinine level, as well as the degree of spinal instability and severity of neurologic deficits. This approach aims to identify patients with better survival outcomes and prioritize their surgical intervention accordingly. Seven factors (serum albumin and alkaline phosphatase levels, international normalized ratio, lymphocyte and neutrophil counts, and the presence of visceral or brain metastases) were considered possible missing items based on five previous validation studies and clinical experience. Artificially missing data were imputed using the missForest imputation technique, which was previously applied and successfully tested to fit the SORG-MLA in validation studies. Discrimination, calibration, overall performance, and decisio...