METHODS: This was a cross-sectional study involving 195 women enrolled in a longitudinal cohort study and seen 20 years after an index birth. All had a standardized patient-administered questionnaire, the International Continence Society Pelvic Organ Prolapse Quantification assessment and 4D translabial ultrasound. Main outcome measures were objective POP clinically and on translabial ultrasound. Postimaging assessment of levator integrity and sonographically determined pelvic organ descent was done blinded against other data.
RESULTS: Of 195 women who were seen a mean of 23 (range, 19.4-46.2) years after their first birth, one declined ultrasound assessment and was excluded, leaving 194. Mean age was 50.2 (range 36.9-66.5) years with a mean body mass index (BMI) of 27.6 (range, 18.3-54.3) kg/m2 . Median parity was 3 (range 1-14). Ninety-one percent (n = 176) had delivered vaginally. Eighteen percent (n = 34) were symptomatic of prolapse. Clinically, 36% (n = 69) had significant POP. Levator avulsion was diagnosed in 16% (n = 31). Mean levator avulsion defect score was 2.2 (range, 0-12). On univariate analysis, levator avulsion and levator avulsion defect score were associated with clinically and sonographically significant POP, that is, odds ratio 2.6 (1.2-5.7), P = .01; and odds ratio 3.3 (1.4-7.7); P = .003, respectively; Ba (P
METHODS: A 3-step framework was proposed, consisting of: (1) 3D LV model reconstruction from motion-corrected 4D cine-MRI; (2) Registration of 2D LGE-MRI with 4D cine-MRI; (3) LV contour extraction from the intersection of LGE slices with the LV model. The framework was evaluated against cardiac MRI data from 27 patients scanned within 6 months after acute myocardial infarction. We compared the use of local Pearson's correlation (LPC) and normalized mutual information (NMI) as similarity measures for the registration. The use of 2 and 6 long-axis (LA) cine-MRI scans was also compared. The accuracy of the framework was evaluated using manual segmentation, and the interobserver variability of the scar volume derived from the segmented LV was determined using Bland-Altman analysis.
RESULTS: LPC outperformed NMI as a similarity measure for the proposed framework using 6 LA scans, with Hausdorrf distance (HD) of 1.19 ± 0.53 mm versus 1.51 ± 2.01 mm (endocardial) and 1.21 ± 0.48 mm versus 1.46 ± 1.78 mm (epicardial), respectively. Segmentation using 2 LA scans was comparable to 6 LA scans with a HD of 1.23 ± 0.70 mm (endocardial) and 1.25 ± 0.74 mm (epicardial). The framework yielded a lower interobserver variability in scar volumes compared with manual segmentation.
CONCLUSION: The framework showed high accuracy and robustness in delineating LV in LGE-MRI and allowed for bidirectional mapping of information between LGE- and cine-MRI scans, crucial in personalized model studies for treatment planning.
METHODS: Computed tomography scans of 102 wrists from 51 healthy individuals were analyzed using a virtualization software. Four anatomical parameters at the distal radius sigmoid notch, namely, the radius of curvature, depth, version angle, and sagittal slope were measured. Morphological patterns of the sigmoid notch surface were identified. The results were statistically analyzed to assess the reliability of the technique and were compared with previously published literature.
RESULTS: Comparing our findings with previously published values, our study revealed a slightly larger radius of curvature and sagittal slope, while revealing a smaller depth and version. We identified the S-type, C-type, and ski-slope morphological variants. The flat-face morphological variant, however, was not identified. The sigmoid notch at the left and right wrists were similar, except for the radius of curvature.
CONCLUSION: This study demonstrates a noninvasive, fast, reliable, and reproducible technique for analyzing the sigmoid notch of the distal radius. In wrist injuries with intact distal radius sigmoid notch but involving comminuted fractures of the ulnar head, ulnar head replacement may be indicated. In such cases, analysis of the ipsilateral intact sigmoid notch would allow us to prepare an ulnar head prosthesis of appropriate size.
RESULTS: The results on the validity of the ACL against IA between the subjects show accurate detection of n, sn, prn, sto, ls and li landmarks. The paired t-test showed that the seven linear measurements were statistically significant when p
METHOD: This study investigates three-dimensional (3D) soft-tissue craniofacial variation, with relation to ethnicity, sex and age variables in British and Irish white Europeans. This utilizes a geometric morphometric approach on a subsampled dataset comprising 292 scans, taken from a Liverpool-York Head Model database. Shape variation and analysis of each variable are tested using 20 anchor anatomical landmarks and 480 sliding semi-landmarks.
RESULTS: Significant ethnicity, sex, and age differences are observed for measurement covering major aspects of the craniofacial shape. The ethnicity shows subtle significant differences compared to sex and age; even though it presents the lowest classification accuracy. The magnitude of dimorphism in sex is revealed in the facial, nasal and crania measurement. Significant shape differences are also seen at each age group, with some distinct dimorphic features present in the age groups.
CONCLUSIONS: The patterns of shape variation show that white British individuals have a more rounded head shape, whereas white Irish individuals have a narrower head shape. White British persons also demonstrate higher classification accuracy. Regarding sex patterns, males are relatively larger than females, especially in the mouth and nasal regions. Females presented with higher classification accuracy than males. The differences in the chin, mouth, nose, crania, and forehead emerge from different growth rates between the groups. Classification accuracy is best for children and senior adult age groups.
RESULTS: This study investigates the effect of iterations in sliding semi-landmarks and their results on the predictive ability in GM analyses of soft-tissue in 3D human face. Principal Component Analysis (PCA) is used for feature selection and the gender are predicted using Linear Discriminant Analysis (LDA) to test the effect of each relaxation state. The results show that the classification accuracy is affected by the number of iterations but not in progressive pattern. Also, there is stability at 12 relaxation state with highest accuracy of 96.43% and an unchanging decline after the 12 relaxation state.
CONCLUSIONS: The results indicate that there is a particular number of iteration or cycle where the sliding becomes optimally relaxed. This means the higher the number of iterations is not necessarily the higher the accuracy.