Automated Cerebral Hemorrhage Detection Using RAPID.

BACKGROUND AND PURPOSE: Intracranial hemorrhage (ICH) is an important event that is diagnosed on head NCCT. Increased NCCT utilization in busy hospitals may limit timely identification of ICH. RAPID ICH is an automated hybrid 2D-3D convolutional neural network application designed to detect ICH that may allow for expedited ICH diagnosis. We determined the accuracy of RAPID ICH for ICH detection and ICH volumetric quantification on NCCT. MATERIALS AND METHODS: NCCT scans were evaluated for ICH by RAPID ICH. Consensus detection of ICH by 3 neuroradiology experts was used as the criterion standard for RAPID ICH comparison. ICH volume was also automatically determined by RAPID ICH in patients with intraparenchymal or intraventricular hemorrhage and compared with manually segmented ICH volumes by a single neuroradiology expert. ICH detection accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and positive and negative likelihood ratios by RAPID ICH were determined. RESULTS: We included 308 studies. RAPID ICH correctly identified 151/158 ICH cases and 143/150 ICH-negative cases, which resulted in high sensitivity (0.956, CI: 0.911-0.978), specificity (0.953, CI: 0.907-0.977), positive predictive value (0.956, CI: 0.911-0.978), and negative predictive value (0.953, CI: 0.907-0.977) for ICH detection. The positive likelihood ratio (20.479, CI 9.928-42.245) and negative likelihood ratio (0.046, CI 0.023-0.096) for ICH detection were similarly favorable. RAPID ICH volumetric quantification for intraparenchymal and intraventricular hemorrhages strongly correlated with expert manual segmentation (correlation coefficient r = 0.983); the median absolute error was 3 mL. CONCLUSIONS: RAPID ICH is highly accurate in the detection of ICH and in the volumetric quantification of intraparenchymal and intraventricular hemorrhages.

Relationship between anteroposterior maxillomandibular morphology and masticatory jaw movement patterns.

The causal relationships between oral function and craniomandibular morphology are poorly understood. The aim of this study was to determine whether quantifiable features of masticatory jaw movements and associated EMG activity correlated with variation in morphology as defined by the ANB angle. Thirty-six healthy subjects with no previous orthodontic treatment, asymptomatic masticatory muscles, and asymptomatic temporomandibular joints participated. While subjects chewed gum, jaw movement data and surface EMG data were digitized and then quantified into a 300 variable vector for each subject. ANB angle measurements were calculated from digitized tracings of lateral cephalographs. Step-wise linear regression and discriminant analyses were used to determine the relationship between the ANB angle and a subset of the variables defining jaw movement patterns and EMG patterns. A linear combination of seven jaw movements and EMG variables accounted for over 75% of the variation in the ANB angle (adjusted x R2 = 0.78, P <.001). A jackknifed cross-validation of the discriminant analysis, which was forced to use the same seven variables as the regression analysis, resulted in correct classification of 14 of 20 skeletal Class I, 7 of 9 skeletal Class II, and 7 of 7 skeletal Class III subjects. These results suggest that there is an association between anteroposterior skeletal morphology, as quantified by the ANB angle, and masticatory jaw movement patterns, as quantified in this study.

Affected-sib-pair analyses reveal support of prior evidence for a susceptibility locus for bipolar disorder, on 21q.

In 22 multiplex pedigrees screened for linkage to bipolar disorder, by use of 18 markers on chromosome 21q, single-locus affected-sib-pair (ASP) analysis detected a high proportion (57%-62%) of alleles shared identical by descent (IBD), with P values of .049-.0008 on nine marker loci. Multilocus ASP analyses revealed locus trios in the distal region between D21S270 and D21S171, with excess allele sharing (nominal P values <.01) under two affection-status models, ASM I (bipolars and schizoaffectives) and ASM II (ASM I plus recurrent unipolars). In addition, under ASM I, the proximal interval spanned by D21S1436 and D21S65 showed locus trios with excess allele sharing (nominal P values of .03-.0003). These findings support prior evidence that a susceptibility locus for bipolar disorder is on 21q.