Postmortem imaging is increasingly used in forensic practice in cases of natural deaths related to cardiovascular diseases, which represent the most common causes of death in developed countries. While radiological examination is generally considered to be a good complement for conventional autopsy, it was thought to have limited application in cardiovascular pathology. At present, multidetector computed tomography (MDCT), CT angiography, and cardiac magnetic resonance imaging (MRI) are used in postmortem radiological investigation of cardiovascular pathologies. This review presents the actual state of postmortem imaging for cardiovascular pathologies in cases of sudden cardiac death (SCD), taking into consideration both the advantages and limitations. The radiological evaluation of ischemic heart disease (IHD), the most frequent cause of SCD in the general population of industrialized countries, includes the examination of the coronary arteries and myocardium. Postmortem CT angiography (PMCTA) is very useful for the detection of stenoses and occlusions of coronary arteries but less so for the identification of ischemic myocardium. MRI is the method of choice for the radiological investigation of the myocardium in clinical practice, but its accessibility and application are still limited in postmortem practice. There are very few reports implicating postmortem radiology in the investigation of other causes of SCD, such as cardiomyopathies, coronary artery abnormalities, and valvular pathologies. Cardiomyopathies representing the most frequent cause of SCD in young athletes cannot be diagnosed by echocardiography, the most widely available technique in clinical practice for the functional evaluation of the heart and the detection of cardiomyopathies. PMCTA and MRI have the potential to detect advanced stages of diseases when morphological substrate is present, but these methods have yet to be sufficiently validated for postmortem cases. Genetically determined channelopathies cannot be detected radiologically. This review underlines the need to establish the role of postmortem radiology in the diagnosis of SCD.

/pdf/postmortem-imaging-of-sudden-cardiac-death-5aafngfw69.pdf

Postmortem imaging of sudden cardiac death

Purpose: The primary aim of the present study was to test the feasibility of predicting diagnostic errors in mammography by merging radiologists’ gaze behavior and image characteristics. A secondary aim was to investigate group-based and personalized predictive models for radiologists of variable experience levels. Methods: The study was performed for the clinical task of assessing the likelihood of malignancy of mammographic masses. Eye-tracking data and diagnostic decisions for 40 cases were acquired from four Radiology residents and two breast imaging experts as part of an IRB-approved pilot study. Gaze behavior features were extracted from the eye-tracking data. Computer-generated and BIRADS images features were extracted from the images. Finally, machine learning algorithms were used to merge gaze and image features for predicting human error. Feature selection was thoroughly explored to determine the relative contribution of the various features. Group-based and personalized user modeling was also investigated. Results: Machine learning can be used to predict diagnostic error by merging gaze behavior characteristics from the radiologist and textural characteristics from the image under review. Leveraging data collected from multiple readers produced a reasonable group model [area under the ROC curve (AUC) = 0.792 ± 0.030]. Personalized user modeling was far more accurate for the more experienced readers (AUC = 0.837 ± 0.029) than for the less experienced ones (AUC = 0.667 ± 0.099). The best performing group-based and personalized predictive models involved combinations of both gaze and image features. Conclusions: Diagnostic errors in mammography can be predicted to a good extent by leveraging the radiologists’ gaze behavior and image content. © 2013 American Association of Physicists in Medicine .[ http://dx.doi.org/10.1118/1.4820536]

Predicting diagnostic error in radiology via eye-tracking and image analytics: preliminary investigation in mammography.

The use of clinical autopsy has been in decline for many years throughout healthcare systems of developed countries despite studies showing substantial discrepancies between autopsy results and pre-mortal clinical diagnoses. We conducted a study to evaluate over time the use and results of clinical autopsies in Sweden. We reviewed the autopsy reports and autopsy referrals of 2410 adult (age > 17) deceased patients referred to two University hospitals in Sweden during two plus two years, a decade apart. There was a decline in the number of autopsies performed over time, however, mainly in one of the two hospitals. The proportion of autopsy referrals from the emergency department increased from 9 to 16%, while the proportion of referrals from regular hospital wards was almost halved. The autopsies revealed a high prevalence of cardiovascular disease, with myocardial infarction and cerebrovascular lesion found in 40% and 19% of all cases, respectively. In a large proportion of cases (> 30%), significant findings of disease were not anticipated before autopsy, as judged from the referral document and additional data obtained in some but not all cases. In accordance with previous research, our study confirms a declining rate of autopsy even at tertiary, academic hospitals and points out factors possibly involved in the decline.

/pdf/cause-of-death-and-significant-disease-found-at-autopsy-4ymgykn59k.pdf

Cause of death and significant disease found at autopsy

The study reports on the evolution of the Australian radiologist relative value unit (RVU) model of measuring radiologist reporting workloads in teaching hospital departments, and aims to outline a way forward for the development of a broad national safety, quality and performance framework that enables value mapping, measurement and benchmarking. The Radiology International Benchmarking Project of Queensland Health provided a suitable high-level national forum where the existing Pitman-Jones RVU model was applied to contemporaneous data, and its shortcomings and potential avenues for future development were analysed. Application of the Pitman-Jones model to Queensland data and also a Victorian benchmark showed that the original recommendation of 40,000 crude RVU per full-time equivalent consultant radiologist (97-98 baseline level) has risen only moderately, to now lie around 45,000 crude RVU/full-time equivalent. Notwithstanding this, the model has a number of weaknesses and is becoming outdated, as it cannot capture newer time-consuming examinations particularly in CT. A significant re-evaluation of the value of medical imaging is required, and is now occurring. We must rethink how we measure, benchmark, display and continually improve medical imaging safety, quality and performance, throughout the imaging care cycle and beyond. It will be necessary to ensure alignment with patient needs, as well as clinical and organisational objectives. Clear recommendations for the development of an updated national reporting workload RVU system are available, and an opportunity now exists for developing a much broader national model. A more sophisticated and balanced multidimensional safety, quality and performance framework that enables measurement and benchmarking of all important elements of health-care service is needed.

The Royal Australian and New Zealand College of Radiologists (RANZCR) relative value unit workload model, its limitations and the evolution to a safety, quality and performance framework

PurposeThis paper aims to examine whether private healthcare entrepreneurship can flourish and overcome obstacles in cases of a free-access public health system and periods of strict public policies, such as the COVID-19 pandemic. Moreover, the paper aims to illuminate the wider social role of private healthcare entrepreneurship during the COVID-19 pandemic.Design/methodology/approachThis paper adopts a qualitative methodological strategy through 12 in-depth semi-structured interviews with the owners of diagnostic centres located in small Greek towns.FindingsPrivate healthcare entrepreneurship flourished and played a significantly positive social role in the context of a degraded public health sector, which lacked investments for more than ten years and was further depleted by its recent focus on COVID-19 incidents. This paper reveals that although public policies that aimed to deal with COVID-19 produced serious consequences, business activity adapted to the new circumstances.Research limitations/implicationsFuture research can combine the findings of this paper with the views of stakeholders, policymakers and social actors.Originality/valueThis paper's value lies in its efforts to expand our current knowledge regarding the impact of COVID-19 public policies on entrepreneurship.

Private healthcare entrepreneurship in a free-access public health system: what was the impact of COVID-19 public policies in Greece?

We propose a comprehensive taxonomy of diagnostic errors in radiology that incorporates requests, image acquisition, radiological reports and evidence of communication to the treating team, and is retrospectively applicable to a given set of radiological episodes using pre-existing standard hospital databases. The taxonomy applies four binary tests to each diagnostic error using widely available hospital records, such as radiological requests, images in Picture Archiving and Communication System, radiological reports and hospital patient records. The taxonomy classifies errors into seven mutually exclusive patterns: no relevant imaging, consistent error (technical non-demonstration), consistent error (human error), ignored correct dissenting radiology result, de novo radiology error (technical non-demonstration), de novo radiology error (human error), and ignored correct confirmatory radiology result. The taxonomy was validated against a set of 250 diagnostic errors identified from an audit of clinical and radiological diagnoses with autopsy as the reference standard. All errors were successfully classified by the taxonomy, and the point of initiation of the error assigned. Of a total of 250 diagnostic errors, 138 (55%) had no relevant imaging performed. Ninety percent of all errors (226) were due to human error only, whether at the stage of clinical suspicion, the radiologist's diagnosis, or afterwards. Of the 112 imaged errors, only 12 (11%) were initiated at diagnostic imaging. The taxonomy of diagnostic error we present is comprehensive, allows retrospective audit of error with commonly available data, and provides clinically useful identification of the point of error initiation.

Diagnostic errors in patients dying in hospital: radiology's contribution.

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Diagnostic errors in patients dying in hospital: radiology's contribution.