An epidemic of pain in an Australian radiology practice

This paper presents findings from a study of an organisationally mandated assimilation process of an enterprise-wide information system in a radiology practice in Australia. A number of interviews with radiologists, radiographers and administrative staff are used to explore the impact of institutional structures on the assimilation process. The case study develops an argument that culture within and outside the Australian Radiology Practice (ARP), social structures within the ARP and organisational-level management mandates have impacted on the assimilation process. The study develops a theoretical framework that integrates elements of social actor theory (Lamb & Kling, 2003) to provide a more fine-grained analysis concentrating on the relationship among the radiology practitioners, the technology (an enterprise-wide Health Information System) and a larger social milieu surrounding its use. This study offers several theoretical and practical implications for technology assimilation in the health and radiology industry regarding the important roles social interactions, individual self-perceptions, organisational mandates and policies can play in assimilating new ICTs.

United we stand, divided we fall: the failure of an accounting information system in a major radiology provider

This article explores the way in which a major Australian radiology organization implemented a complex accounting information system and how workers in the 72 radiology practises that had to use it resisted the change. The study reports on the issues that led to the circumvention of the system by individuals and, after only three years, complete withdrawal of the accounting information system by the parent organization. This article has implications for firms in the health care and other sectors considering implementing new accounting information systems. Organizations need to incorporate change management techniques and provide open communication to all stakeholders to minimize disruption and potential problems.

Clinician-driven automated classification of limb fractures from free-text radiology reports

The aim of this research is to report initial experimental results and evaluation of a clinician-driven automated method that can address the issue of misdiagnosis from unstructured radiology reports. Timely diagnosis and reporting of patient symptoms in hospital emergency departments (ED) is a critical component of health services delivery. However, due to disperse information resources and vast amounts of manual processing of unstructured information, a point-of-care accurate diagnosis is often difficult. A rule-based method that considers the occurrence of clinician specified keywords related to radiological findings was developed to identify limb abnormalities, such as fractures. A dataset containing 99 narrative reports of radiological findings was sourced from a tertiary hospital. The rule-based method achieved an F-measure of 0.80 and an accuracy of 0.80. While our method achieves promising performance, a number of avenues for improvement were identified using advanced natural language processing (NLP) techniques.

Automatic classification of free-text radiology reports to identify limb fractures using machine learning and the SNOMED CT ontology

Objective To develop and evaluate machine learning techniques that identify limb fractures and other abnormalities (e.g. dislocations) from radiology reports. Materials and Methods 99 free-text reports of limb radiology examinations were acquired from an Australian public hospital. Two clinicians were employed to identify fractures and abnormalities from the reports; a third senior clinician resolved disagreements. These assessors found that, of the 99 reports, 48 referred to fractures or abnormalities of limb structures. Automated methods were then used to extract features from these reports that could be useful for their automatic classification. The Naive Bayes classification algorithm and two implementations of the support vector machine algorithm were formally evaluated using cross-fold validation over the 99 reports. Result Results show that the Naive Bayes classifier accurately identifies fractures and other abnormalities from the radiology reports. These results were achieved when extracting stemmed token bigram and negation features, as well as using these features in combination with SNOMED CT concepts related to abnormalities and disorders. The latter feature has not been used in previous works that attempted classifying free-text radiology reports. Discussion Automated classification methods have proven effective at identifying fractures and other abnormalities from radiology reports (F-Measure up to 92.31%). Key to the success of these techniques are features such as stemmed token bigrams, negations, and SNOMED CT concepts associated with morphologic abnormalities and disorders. Conclusion This investigation shows early promising results and future work will further validate and strengthen the proposed approaches.

Automated classification of limb fractures from free-text radiology reports using a clinician-informed gazetteer methodology

Background Timely diagnosis and reporting of patient symptoms in hospital emergency departments (ED) is a critical component of health services delivery. However, due to dispersed information resources and a vast amount of manual processing of unstructured information, accurate point-of-care diagnosis is often difficult. Aims The aim of this research is to report initial experimental evaluation of a clinician-informed automated method for the issue of initial misdiagnoses associated with delayed receipt of unstructured radiology reports. Method A method was developed that resembles clinical reasoning for identifying limb abnormalities. The method consists of a gazetteer of keywords related to radiological findings; the method classifies an X-ray report as abnormal if it contains evidence contained in the gazetteer. A set of 99 narrative reports of radiological findings was sourced from a tertiary hospital. Reports were manually assessed by two clinicians and discrepancies were validated by a third expert ED clinician; the final manual classification generated by the expert ED clinician was used as ground truth to empirically evaluate the approach. Results The automated method that attempts to individuate limb abnormalities by searching for keywords expressed by clinicians achieved an F-measure of 0.80 and an accuracy of 0.80. Conclusion While the automated clinician-driven method achieved promising performances, a number of avenues for improvement were identified using advanced natural language processing (NLP) and machine learning techniques.

Cone beam computed tomography in oral radiology

In dentistry, basic imaging techniques such as intraoral and panoramic radiography are in most cases the only imaging techniques required for the detection of pathology. Conventional intraoral radiographs provide images with sufficient information for most dental radiographic needs. Panoramic radiography produces a single image of both jaws, giving an excellent overview of oral hard tissues. Regardless of the technique, plain radiography has only a limited capability in the evaluation of three-dimensional (3D) relationships. Technological advances in radiological imaging have moved from two-dimensional (2D) projection radiography towards digital, 3D and interactive imaging applications. This has been achieved first by the use of conventional computed tomography (CT) and more recently by cone beam CT (CBCT). CBCT is a radiographic imaging method that allows accurate 3D imaging of hard tissues. CBCT has been used for dental and maxillofacial imaging for more than ten years and its availability and use are increasing continuously. However, at present, only best practice guidelines are available for its use, and the need for evidence-based guidelines on the use of CBCT in dentistry is widely recognized. We evaluated (i) retrospectively the use of CBCT in a dental practice, (ii) the accuracy and reproducibility of pre-implant linear measurements in CBCT and multislice CT (MSCT) in a cadaver study, (iii) prospectively the clinical reliability of CBCT as a preoperative imaging method for complicated impacted lower third molars, and (iv) the tissue and effective radiation doses and image quality of dental CBCT scanners in comparison with MSCT scanners in a phantom study. Using CBCT, subjective identification of anatomy and pathology relevant in dental practice can be readily achieved, but dental restorations may cause disturbing artefacts. CBCT examination offered additional radiographic information when compared with intraoral and panoramic radiographs. In terms of the accuracy and reliability of linear measurements in the posterior mandible, CBCT is comparable to MSCT. CBCT is a reliable means of determining the location of the inferior alveolar canal and its relationship to the roots of the lower third molar. CBCT scanners provided adequate image quality for dental and maxillofacial imaging while delivering considerably smaller effective doses to the patient than MSCT. The observed variations in patient dose and image quality emphasize the importance of optimizing the imaging parameters in both CBCT and MSCT.

A Benefit-Risk Assessment Framework for Development of Clinical Guidelines in Diagnostic Radiology

Thesis (Ph.D.)--University of Washington, 2015-12

Thermoluminescence measurements of entrance surface skin dose in exams of dog's chest in veterinary radiology

This study aims to determine the entrance surface skin doses in dogs (with suspected pulmonary metastasis) submitted to chest X-rays using the technique of thermoluminescence (TL) dosimetry. Twenty seven radiologic exams of dogs of different breed and sizes were performed. The radiation doses were assessed using thermoluminescent dosimeters of calcium sulphate doped with dysprosium (CaSO(4):Dy) produced at Instituto de Pesquisas Energeticas e Nucleares (IPEN-CNEN). The entrance surface skin dose range evaluated in this type of procedure was between 0.43 mGy to small size dogs and 4.22 mGy to big size dogs with repeated exams. The obtained results indicate that is extremely important the assessment of radiation doses involved in veterinary diagnostic radiology procedures, to evaluate the delivered doses to the animals, to be used as a parameter in the individual monitoring of pet's owners, who assist the animal positioning, and to protect occupationally exposed workers at the Veterinary Radiology Clinics. (C) 2010 Elsevier Ltd. All rights reserved.

Study of entrance surface skin dose in veterinary radiology

This study aims the evaluation of the radiation dose levels involved in veterinary radiology and to contribute to review the procedures for performing radiographic exams in animals in the Department of Veterinary Radiology of Faculdade de Medicina Veterinária e Zootecnia of Universidade Estadual Paulista (FMVZ-UNESP/Brazil). The obtained results has shown to be extremely important the assessment of doses involved in veterinary diagnostic radiology procedures both to protect the occupationally exposed workers and to optimize the delivered doses to the animals. © 2009 Springer-Verlag.