Initial clinical results for breath-hold CT-based processing of respiratory-gated PET acquisitions

Purpose  Respiratory motion causes uptake in positron emission tomography (PET) images of chest structures to spread out and misregister with the CT images. This misregistration can alter the attenuation correction and thus the quantisation of PET images. In this paper, we present the first clinical results for a respiratory-gated PET (RG-PET) processing method based on a single breath-hold CT (BH-CT) acquisition, which seeks to improve diagnostic accuracy via better PET-to-CT co-registration. We refer to this method as “CT-based” RG-PET processing. Methods  Thirteen lesions were studied. Patients underwent a standard clinical PET protocol and then the CT-based protocol, which consists of a 10-min List Mode RG-PET acquisition, followed by a shallow end-expiration BH-CT. The respective performances of the CT-based and clinical PET methods were evaluated by comparing the distances between the lesions’ centroids on PET and CT images. SUV_MAX and volume variations were also investigated. Results  The CT-based method showed significantly lower (p = 0.027) centroid distances (mean change relative to the clinical method = −49%; range = −100% to 0%). This led to higher SUV_MAX (mean change = +33%; range = −4% to 69%). Lesion volumes were significantly lower (p = 0.022) in CT-based PET volumes (mean change = −39%: range = −74% to −1%) compared with clinical ones. Conclusions  A CT-based RG-PET processing method can be implemented in clinical practice with a small increase in radiation exposure. It improves PET-CT co-registration of lung lesions and should lead to more accurate attenuation correction and thus SUV measurement.     

Best evidence in anesthetic practice

Question  

In postoperative non-ventilated patients, what is the efficacy and harm of pharmacological interventions in treating postoperative shivering?     

Innovative Power of Health Care Organisations Affects IT Adoption: A bi-National Health IT Benchmark Comparing Austria and Germany

Multinational health IT benchmarks foster cross-country learning and have been employed at various levels, e.g. OECD and Nordic countries. A bi-national benchmark study conducted in 2007 revealed a significantly higher adoption of health IT in Austria compared to Germany, two countries with comparable healthcare systems. We now investigated whether these differences still persisted. We further studied whether these differences were associated with hospital intrinsic factors, i.e. the innovative power of the organisation and hospital demographics. We thus performed a survey to measure the “perceived IT availability” and the “innovative power of the hospital” of 464 German and 70 Austrian hospitals. The survey was based on a questionnaire with 52 items and was given to the directors of nursing in 2013/2014. Our findings confirmed a significantly greater IT availability in Austria than in Germany. This was visible in the aggregated IT adoption composite score “IT function” as well as in the IT adoption for the individual functions “nursing documentation” (OR?=?5.98), “intensive care unit (ICU) documentation” (OR?=?2.49), “medication administration documentation” (OR?=?2.48), “electronic archive” (OR?=?2.27) and “medication” (OR?=?2.16). “Innovative power” was the strongest factor to explain the variance of the composite score “IT function”. It was effective in hospitals of both countries but significantly more effective in Austria than in Germany. “Hospital size” and “hospital system affiliation” were also significantly associated with the composite score “IT function”, but they did not differ between the countries. These findings can be partly associated with the national characteristics. Indicators point to a more favourable financial situation in Austrian hospitals; we thus argue that Austrian hospitals may possess a larger degree of financial freedom to be innovative and to act accordingly. This study is the first to empirically demonstrate the effect of “innovative power” in hospitals on health IT adoption in a bi-national health IT benchmark. We recommend directly including the financial situation into future regression models. On a political level, measures to stimulate the “innovative power” of hospitals should be considered to increase the digitalisation of healthcare.     

A Belief Rule Based Expert System to Assess Tuberculosis under Uncertainty

The primary diagnosis of Tuberculosis (TB) is usually carried out by looking at the various signs and symptoms of a patient. However, these signs and symptoms cannot be measured with 100 % certainty since they are associated with various types of uncertainties such as vagueness, imprecision, randomness, ignorance and incompleteness. Consequently, traditional primary diagnosis, based on these signs and symptoms, which is carried out by the physicians, cannot deliver reliable results. Therefore, this article presents the design, development and applications of a Belief Rule Based Expert System (BRBES) with the ability to handle various types of uncertainties to diagnose TB. The knowledge base of this system is constructed by taking experts’ suggestions and by analyzing historical data of TB patients. The experiments, carried out, by taking the data of 100 patients demonstrate that the BRBES’s generated results are more reliable than that of human expert as well as fuzzy rule based expert system.     

Disparities in Geographic Accessibility of National Cancer Institute Cancer Centers in the United States

The National Cancer Institute (NCI) Cancer Centers form the backbone of the cancer care system in the United States since their inception in the early 1970s. Most studies on their geographic accessibility used primitive measures, and did not examine the disparities across urbanicity or demographic groups. This research uses an advanced accessibility method, termed “2-step floating catchment area (2SFCA)” and implemented in Geographic Information Systems (GIS), to capture the degree of geographic access to NCI Cancer Centers by accounting for competition intensity for the services and travel time between residents and the facilities. The results indicate that urban advantage is pronounced as the average accessibility is highest in large central metro areas, declines to large fringe metro, medium metro, small metro, micropolitan and noncore rural areas. Population under the poverty line are disproportionally concentrated in lower accessibility areas. However, on average Non-Hispanic White have the lowest geographic accessibility, followed by Hispanic, Non-Hispanic Black and Asian, and the differences are statistically significant. The “reversed racial disadvantage” in NCI Cancer Center accessibility seems counterintuitive but is consistent with an influential prior study; and it is in contrast to the common observation of co-location of concentration of minority groups and people under the poverty line.