Objectives: Magnetic resonance imaging (MRI) is the definitive investigation for detection of an acoustic neuroma. It is however an expensive resource, and pick-up rate of a tumor can be as low as 1% of all patients scanned. This study aims to examine referral patterns for MRI screening for patients presenting with asymmetrical sensorineural hearing loss (ASHL). A second aim was to suggest appropriate screening criteria.
Method: All 132 MRI scans performed for ASHL in the year 2005 were reviewed retrospectively along with their case records and audiograms. In addition, MRI scans and case records were reviewed for the last 30 patients diagnosed with acoustic neuromas. Information was analyzed using 2 published protocols and additional frequency-specific defined criteria.
Results: Two acoustic neuromas were picked up out of 132 scans performed. Of the scans performed for ASHL, a third did not fit with any of the published criteria. Of the 30 positive scans for a tumor, the patients/audiograms revealed that 10% did not fit the published criteria despite the patients having no other audiovestibular symptoms.
Conclusions: There appears to be no universally accepted guidelines on screening in ASHL with clinical acumen being used by most ENT consultants in this region. Applying protocols may reduce the amount of scans performed, but up to 10% of tumors may be missed by this approach.
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http://dx.doi.org/10.1016/j.amjoto.2009.02.005 | DOI Listing |
Knee Surg Sports Traumatol Arthrosc
January 2025
Sports Medicine Service, Beijing Jishuitan Hospital, Capital Medical University, Beijing, China.
Purpose: To propose a new sign of patellar maltracking in recurrent patellar dislocation (RPD) and compare the differences in lower limb rotational and bony structural abnormalities among the different signs.
Patients And Methods: A retrospective study included 279 patients (mean age: 22 years; female: 81%) who underwent primary surgery for RPD over the past 4 years was performed. The patients were grouped based on the characteristics of patellar tracking: low-, moderate- and high-grade J-sign.
Eur J Radiol Open
June 2025
Department of Nuclear Medicine, Medical Faculty and University Hospital Duesseldorf, Heinrich Heine University Duesseldorf, Düsseldorf 40225, Germany.
Objective: [F]FDG imaging is an integral part of patient management in CAR-T-cell therapy for recurrent or therapy-refractory DLBCL. The calculation methods of predictive power of specific imaging parameters still remains elusive. With this retrospective study, we sought to evaluate the predictive power of the baseline metabolic parameters and tumor burden calculated with automated segmentation via different thresholding methods for early therapy failure and mortality risk in DLBCL patients.
View Article and Find Full Text PDFRegen Biomater
November 2024
Department of Oral and Maxillofacial Surgery, Faculty of Dentistry, Prince of Songkla University, Hatyai 90110, Thailand.
Alveolar ridge loss presents difficulties for implant placement and stability. To address this, alveolar ridge preservation (ARP) is required to maintain bone and avoid the need for ridge augmentation using socket grafting. In this study, a scaffold for ARP was created by fabricating a 3D porous dense microfiber silk fibroin (mSF) embedded in poly(vinyl alcohol) (PVA), which mimics the osteoid template.
View Article and Find Full Text PDFCureus
December 2024
Emergency Medicine, University of Alabama at Birmingham, Birmingham, USA.
Access to diagnostic imaging is significantly limited in much of the world, and sub-Saharan Africa is no exception. Clinician-performed point-of-care ultrasound (POCUS) may provide increased access to diagnostic imaging for many patients in low-resource settings, but training in this modality is limited. We describe the development and implementation of a context-specific, multi-modal pilot POCUS curriculum involving hands-on instruction, in-person and online didactics, asynchronous online image review, and quantitative evaluation.
View Article and Find Full Text PDFFront Med (Lausanne)
December 2024
Software Engineering Department, LUT University, Lahti, Finland.
Introduction: Neurodegenerative diseases, including Parkinson's, Alzheimer's, and epilepsy, pose significant diagnostic and treatment challenges due to their complexity and the gradual degeneration of central nervous system structures. This study introduces a deep learning framework designed to automate neuro-diagnostics, addressing the limitations of current manual interpretation methods, which are often time-consuming and prone to variability.
Methods: We propose a specialized deep convolutional neural network (DCNN) framework aimed at detecting and classifying neurological anomalies in MRI data.
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