Objective: To explore the feasibility of dynamic three-dimensional ultrasound measurement in the diagnosis of pelvic floor dyssynergia(PFD).
Methods: Thirty female patients with PFD received dynamic three-dimensional ultrasound. The differences in angle α measured by transperineal three-dimensional ultrasound, and angle β, angle γ, and H line as measured by transanorectal three-dimensional ultrasound were compared between resting state and Valsalva maneuver. In addition, the detective rate of PFD by different parameters was analyzed.
Results: In 30 patients, rectocele was found in 13 cases(43.3%), rectal internal mucous intussusception in 14 cases(46.7%), uterine prolapse in 11 cases(36.7%), and bladder prolapse in 1 case(3.3%). Compared with the resting state, α, β and H decreased obviously, but γ increased apparently in Valsalva maneuver, and differences of these parameters were statistically significant(all P<0.01). Detective rates of PFD for parameters of α, β, γ and H were 93.3%(28/30), 96.7%(29/30), 96.7%(29/30) and 86.7%(26/30), respectively.
Conclusion: Measurements of α, β, γ and H can provide feasible indicators for clinical diagnosis of PFD.
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Cureus
December 2024
Diagnostic Radiology, University of Washington, Seattle, USA.
Introduction: Cervical foraminotomy is a procedure used to treat patients with radiculopathy. While the procedure can be performed using a minimally invasive technique, achieving complete visualization of relevant anatomy can be challenging. This study explores the use of patient-specific three-dimensional (3D) printed anatomical models, created from advanced medical imaging data, for preoperative planning and intraoperative guidance in cervical foraminotomy by comparing fluoroscopy time, operative time, estimated blood loss volume, and functional improvement.
View Article and Find Full Text PDFPeerJ
January 2025
Section of Orthodontics and Craniofacial Biology, Department of Dentistry, Radboud University Medical Center, Nijmegen, Netherlands.
Aim: To compare three-dimensional (3D) facial morphology of various unilateral cleft subphenotypes at 9-years of age to normative data using a general face template and automatic landmarking. The secondary objective is to compare facial morphology of 9-year-old children with unilateral fusion to differentiation defects.
Methods: 3D facial stereophotogrammetric images of 9-year-old unilateral cleft patients were imported into 3DMedX® for processing.
Clin Oral Investig
January 2025
Department of Prosthetic Dentistry, LMU University Hospital, LMU Munich, Goethestrasse 70, 80336, Munich, Germany.
Objective: Evaluation of the accuracy of direct digitization of maxillary scans depending on the scanning strategy.
Materials And Methods: A maxillary model with a metal bar as a reference structure fixed between the second molars was digitized using the CEREC Primescan AC scanner (N = 225 scans). Nine scanning strategies were selected (n = 25 scans per strategy), differing in scan area segmentation (F = full jaw, H = half jaw, S = sextant) and scan movement pattern (L = linear, Z = zig-zag, C = combined).
J Thorac Cardiovasc Surg
January 2025
Division of Cardiology, The Hospital for Sick Children, Toronto, ON, Canada; Center for Image Guided Innovation and Therapeutic Intervention, The Hospital for Sick Children, Toronto, ON, Canada.
Objectives: Mixed reality (MixR) is an innovative visualization tool that presents virtual elements in a real-world environment, enabling real-time interaction between the user and the combined digital/physical reality. We aimed to explore the feasibility of MixR in enhancing preoperative planning and intraoperative guidance for the correction of various complex congenital heart defects (CHDs).
Methods: Patients underwent cardiac computed tomography or cardiac magnetic resonance and segmentation of digital imaging and communications in medicine (DICOM) images was performed.
Clin Oral Investig
January 2025
State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, Sichuan, 610041, China.
Objectives: To develop a platform including a deep convolutional neural network (DCNN) for automatic segmentation of the maxillary sinus (MS) and adjacent structures, and automatic algorithms for measuring 3-dimensional (3D) clinical parameters.
Materials And Methods: 175 CBCTs containing 242 MS were used as the training, validating and testing datasets at the ratio of 7:1:2. The datasets contained healthy MS and MS with mild (2-4 mm), moderate (4-10 mm) and severe (10- mm) mucosal thickening.
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