Publications by authors named "H C Addley"
Aim: Three rounds of industrial action (IA) were carried out by junior doctors in the United Kingdom between March and June 2023. We investigated the impact of radiology registrars undertaking IA on the efficiency of a large teaching hospital's radiology department.
Materials And Methods: This service evaluation was registered with the local Quality Surveillance Information System and involved analysing data pertaining to the computed tomography, magnetic resonance imaging, ultrasound, and x-ray studies performed before, during, and after periods of IA.
Numerous conditions can mimic ovarian malignancy. Identifying the origin of a pelvic mass or disseminated peritoneal abnormality on imaging is important to ensure that the patient receives optimal management by the appropriate clinical team. Ovarian cancer mimics include infections and other neoplastic processes, for example, actinomycosis, lymphoma, and sarcoma.
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- * Researchers developed a machine learning model that combines clinical, blood-based, and radiomic data from patients to predict changes in disease volume after NACT, achieving an 8% improvement in prediction accuracy when integrating radiomics.
- * The study shows the importance of using radiomics in patient response models, offering a potential path for creating new clinical trial methods focused on biomarkers in HGSOC treatment.
Objectives: To investigate the relationship between magnetization transfer (MT) imaging and tissue macromolecules in high-grade serous ovarian cancer (HGSOC) and whether MT ratio (MTR) changes following neoadjuvant chemotherapy (NACT).
Methods: This was a prospective observational study. 12 HGSOC patients were imaged before treatment.
Background: Pathological response to neoadjuvant treatment for patients with high-grade serous ovarian carcinoma (HGSOC) is assessed using the chemotherapy response score (CRS) for omental tumor deposits. The main limitation of CRS is that it requires surgical sampling after initial neoadjuvant chemotherapy (NACT) treatment. Earlier and non-invasive response predictors could improve patient stratification.
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