This paper reviews the use of an intracavitary mold in the radiotherapeutic management of recurrent sub-orbital carcinoma of the maxillary sinus. An overview of the clinical features of antral carcinomas and the concept of brachytherapy in the management of these lesions is presented. Brachytherapy is usually reserved for relatively accessible lesions. Post-surgical and radiation-induced trismus can be a complicating factor, as in the case presented, where the inter-incisal distance was less than three millimeters. To circumvent the problem, a multi-layer antral plug was utilized as a carrier for the radioactive sources, and its construction is described.

Download full-text PDF

Source
http://dx.doi.org/10.1111/j.1754-4505.1993.tb01466.xDOI Listing

Publication Analysis

Top Keywords

utilization multi-layer
4
multi-layer prosthesis
4
prosthesis treat
4
treat recurrent
4
recurrent antral
4
antral carcinoma
4
carcinoma case
4
case report
4
report review
4
review literature
4

Similar Publications

Multi-channel spatio-temporal graph attention contrastive network for brain disease diagnosis.

Neuroimage

January 2025

College of Artificial Intelligence, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, China; Key Laboratory of Brain-Machine Intelligence Technology, Ministry of Education, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, China. Electronic address:

Dynamic brain networks (DBNs) can capture the intricate connections and temporal evolution among brain regions, becoming increasingly crucial in the diagnosis of neurological disorders. However, most existing researches tend to focus on isolated brain network sequence segmented by sliding windows, and they are difficult to effectively uncover the higher-order spatio-temporal topological pattern in DBNs. Meantime, it remains a challenge to utilize the structure connectivity prior in the DBNs analysis.

View Article and Find Full Text PDF

Background: In the last years, artificial intelligence (AI) has contributed to improving healthcare including dentistry. The objective of this study was to develop a machine learning (ML) model for early childhood caries (ECC) prediction by identifying crucial health behaviours within mother-child pairs.

Methods: For the analysis, we utilized a representative sample of 724 mothers with children under six years in Bangladesh.

View Article and Find Full Text PDF

Background: One of the most challenging cancers is triple-negative breast cancer, which is subdivided into many molecular subtypes. Due to the high degree of heterogeneity, the role of precision medicine remains challenging. With the use of machine learning (ML)-guided gene selection, the differential gene expression analysis can be optimized, and eventually, the process of precision medicine can see great advancement through biomarker discovery.

View Article and Find Full Text PDF

Estimating seismic anisotropy parameters, such as Thomson's parameters, is crucial for investigating fractured and finely layered geological media. However, many inversion methods rely on complex physical models with initial assumptions, leading to non-reproducible estimates and subjective fracture interpretation. To address these limitations, this study utilizes machine learning methods: support vector regression, extreme gradient boost, multi-layer perceptron, and a convolutional neural network.

View Article and Find Full Text PDF

Electrocardiogram (ECG) signals contain complex and diverse features, serving as a crucial basis for arrhythmia diagnosis. The subtle differences in characteristics among various types of arrhythmias, coupled with class imbalance issues in datasets, often hinder existing models from effectively capturing key information within these complex signals, leading to a bias towards normal classes. To address these challenges, this paper proposes a method for arrhythmia classification based on a multi-branch, multi-head attention temporal convolutional network (MB-MHA-TCN).

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!