Prognosis Prediction in Head and Neck Squamous Cell Carcinoma by Radiomics and Clinical Information.

(1) Background: head and neck squamous cell carcinoma (HNSCC) is a common cancer whose prognosis is affected by its heterogeneous nature. We aim to predict 5-year overall survival in HNSCC radiotherapy (RT) patients by integrating radiomic and clinical information in machine-learning models; (2) Methods: HNSCC radiotherapy planning computed tomography (CT) images with RT structures were obtained from The Cancer Imaging Archive. Radiomic features and clinical data were independently analyzed by five machine-learning algorithms.

Radiomics-Clinical AI Model with Probability Weighted Strategy for Prognosis Prediction in Non-Small Cell Lung Cancer.

In this study, we propose a radiomics clinical probability-weighted model for the prediction of prognosis for non-small cell lung cancer (NSCLC). The model combines radiomics features extracted from radiotherapy (RT) planning images with clinical factors such as age, gender, histology, and tumor stage. CT images with radiotherapy structures of 422 NSCLC patients were retrieved from The Cancer Imaging Archive (TCIA).

Prognostic Prediction of Cancer Based on Radiomics Features of Diagnostic Imaging: The Performance of Machine Learning Strategies.

Tumor phenotypes can be characterized by radiomics features extracted from images. However, the prediction accuracy is challenged by difficulties such as small sample size and data imbalance. The purpose of the study was to evaluate the performance of machine learning strategies for the prediction of cancer prognosis.

Radiomics from Various Tumour Volume Sizes for Prognosis Prediction of Head and Neck Squamous Cell Carcinoma: A Voted Ensemble Machine Learning Approach.

Background: Traditionally, cancer prognosis was determined by tumours size, lymph node spread and presence of metastasis (TNM staging). Radiomics of tumour volume has recently been used for prognosis prediction. In the present study, we evaluated the effect of various sizes of tumour volume.

Radiomics-Based Artificial Intelligence Differentiation of Neurodegenerative Diseases with Reference to the Volumetry.

Unlabelled: This study aimed to build automated detection models-one by brain regional volume (V-model), and the other by radiomics features of the whole brain (R-model)-to differentiate mild cognitive impairment (MCI) from cognitive normal (CN), and Alzheimer's Disease (AD) from mild cognitive impairment (MCI). The objectives are to compare the models and identify whether radiomics or volumetry can provide a better prediction for differentiating different types of dementia.

Method: 582 MRI T1-weighted images were retrieved from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, which is a multicenter operating open source database for AD.

Multimodal Patient-Specific Registration for Breast Imaging Using Biomechanical Modeling with Reference to AI Evaluation of Breast Tumor Change.

Background: The strategy to combat the problem associated with large deformations in the breast due to the difference in the medical imaging of patient posture plays a vital role in multimodal medical image registration with artificial intelligence (AI) initiatives. How to build a breast biomechanical model simulating the large-scale deformation of soft tissue remains a challenge but is highly desirable.

Methods: This study proposed a hybrid individual-specific registration model of the breast combining finite element analysis, property optimization, and affine transformation to register breast images.

Accurate Age Determination for Adolescents Using Magnetic Resonance Imaging of the Hand and Wrist with an Artificial Neural Network-Based Approach.

This study proposes an accurate method in assessing chronological age of the adolescents using a machine learning approach using MRI images. We also examined the value of MRI with Tanner-Whitehouse 3 (TW3) method in assessing skeletal maturity. Seventy-nine 12-17-year-old healthy Hong Kong Chinese adolescents were recruited.

Effects of Panax ginseng-containing herbal plasters on compressed intervertebral discs in an in vivo rat tail model.

Background: Tienchi (Panax notoginseng) has been used in conservative treatments for back pain as a major ingredient of many herbal medicines. This study aims to investigate the effects of a herbal medicine containing tienchi on compressed intervertebral discs in rats.

Methods: Using an in vivo rat tail model, intervertebral disc compression was simulated in the caudal 8-9 discs of 25 rats by continuous static compression (11 N) for 2 weeks.

Development of a prototype of the tele-localisation system in radiotherapy using personal digital assistant via wireless communication.

In localisation of radiotherapy treatment field, the oncologist is present at the simulator to approve treatment details produced by the therapist. Problems may arise if the oncologist is not available and the patient requires urgent treatment. The development of a tele-localisation system is a potential solution, where the oncologist uses a personal digital assistant (PDA) to localise the treatment field on the image sent from the simulator through wireless communication and returns the information to the therapist after his or her approval.

An image feature approach for computer-aided detection of ischemic stroke.

We present a computer-aided detection (CAD) scheme for early detection of ischemic stroke with small lesions using image feature characteristics. A novel Circular Adaptive Region of Interest (CAROI) method is proposed to analyze the Computed Tomography (CT) images of the brain. Our result indicates that for the emergency physicians and radiology residents, there is a significant improvement in sensitivity and specificity when using CAD (P < 0.

The calculation of dose enhancement close to platinum implants for skull radiography.

Materials with high atomic numbers experience the occurrence of the photoelectric effect when they are irradiated by low energy photons. A short range dose enhancement, due to the dominant photoelectric effect, close to platinum implants (Z = 78) in diagnostic radiography cannot be easily measured experimentally. The enhanced dose may increase the risk for adverse health effects from cancer or may damage vital brain structures close to the high atomic number implants.

Computer-generated index for evaluation of idiopathic scoliosis in digital chest images: a comparison with digital measurement.

An intelligence system was used to generate index for scoliosis. Tests were designed to evaluate the consistency of the automatic computer-generated index and to quantify the correlation between Cobb angle and computer generated scoliosis classification index (SCI). A fully automatic computer-generated index can be used to assess the extent of spinal curvature rather than manual measurement on radiographs.

A mobile phone integrated health care delivery system of medical images.

With the growing computing capability of mobile phones, a handy mobile controller is developed for accessing the picture archiving and communication system (PACS) to enhance image management for clinicians with nearly no restriction in time and location using various wireless communication modes. The PACS is an integrated system for the distribution and archival of medical images that are acquired by different imaging modalities such as CT (computed tomography) scanners, CR (computed radiography) units, DR (digital radiography) units, US (ultrasonography) scanners, and MR (magnetic resonance) scanners. The mobile controller allows image management of the PACS including display, worklisting, query and retrieval of medical images in DICOM format.