Life cycle costing of MRI machine at a tertiary care teaching hospital

MRI scarcity in low- and middle-income countries

Since the introduction of MRI as a sustainable diagnostic modality, global accessibility to its services has revealed a wide discrepancy between populations-leaving most of the population in LMICs without access to this important imaging modality. Several factors lead to the scarcity of MRI in LMICs; for example, inadequate infrastructure and the absence of a dedicated workforce are key factors in the scarcity observed. RAD-AID has contributed to the advancement of radiology globally by collaborating with our partners to make radiology more accessible for medically underserved communities. However, progress is slow and further investment is needed to ensure improved global access to MRI.

Depression screening using a non-verbal self-association task: A machine-learning based pilot study

BACKGROUND

Effective screening is important to combat the raising burden of depression and opens a critical time window for early intervention. Clinical use of non-verbal depression screening is nascent, yet a promising and viable candidate to supplement verbal screening. Differential self- and emotion-processing in depression patients were previously reported by non-verbal behavioural assessments, corroborated by neuroimaging findings of distinct neuroanatomical markers. Thus non-verbal validated brain-behaviour based self-emotion-related assessment data reflect physiological differences and may support individual level screening of depression.

METHODS

In this pilot study (n = 84) we collected two longitudinal sessions of behavioural assessment data in a laboratory setting. Depression was assessed using Beck Depression Inventory II (BDI-II), to explore optimal screening methods with machine-learning, and to establish the validity of adapting a novel behavioural assessment focusing on self and emotions for depression screening.

RESULTS

The best machine-learning model achieved high performance in depression screening, 10-Fold cross-validation (CV) Area Under the receiver operating characteristic Curve (AUC) of 0.90 and balanced accuracy of 0.81, using a Gradient Boosting algorithm. Prospective prediction using a model trained with session 1 data to predict session 2 depression status achieved a 10-Fold CV AUC of 0.77 and balanced accuracy of 0.66. We also identified interpretable behavioural signatures for depression patients based on the best model.

CONCLUSION

The study supports the utility of using behavioural data as a viable and cost-effective solution for depression screening, with a potential wide range of applications in clinical settings.

Cost-Effectiveness of Life Cycle Cost Theory-Based Large Medical Equipment

The purpose of this study is to use the life cycle cost theory to analyze the efficiency of large medical equipment in hospitals, so as to implement life cycle cost (LCC) management and solve the current problems in hospitals. The analysis model of cost benefit of large medical equipment is established, and the cost-effectiveness of 4 large medical equipment between 2019 and 2021 is investigated and analyzed. In terms of the data in each information system of hospitals, the utilization of large medical equipment is quantitatively evaluated and analyzed by life cycle theory. The results show that the Revolution 256 row has the highest revenue of 113.29%. The annual depreciation of Signa 3.0 T HDxt is the highest, amounting to 4,160,000 yuan. However, there is lack of quality control and preventive maintenance of most equipment during use. The cost and benefit of large medical equipment in hospitals are analyzed, which demonstrates that Signa 3.0 T HDxt shows better effectiveness. Too high hospital warranty cost reflects the weak maintenance strength of hospital engineering technicians. The fundamental point of the maintenance and management of large medical equipment is to strengthen the performance evaluation of medical engineering technicians.

Sustainable low-field cardiovascular magnetic resonance in changing healthcare systems

Cardiovascular disease continues to be a major burden facing healthcare systems worldwide. In the developed world, cardiovascular magnetic resonance (CMR) is a well-established non-invasive imaging modality in the diagnosis of cardiovascular disease. However, there is significant global inequality in availability and access to CMR due to its high cost, technical demands as well as existing disparities in healthcare and technical infrastructures across high-income and low-income countries. Recent renewed interest in low-field CMR has been spurred by the clinical need to provide sustainable imaging technology capable of yielding diagnosticquality images whilst also being tailored to the local populations and healthcare ecosystems. This review aims to evaluate the technical, practical and cost considerations of low field CMR whilst also exploring the key barriers to implementing sustainable MRI in both the developing and developed world.

Capturing patient anatomy for designing and manufacturing personalized prostheses

Prostheses play a critical role in healthcare provision for many patients and encompass aesthetic facial prostheses, prosthetic limbs and prosthetic joints, bones, and other implantable medical devices in musculoskeletal surgery. An increasingly important component in cutting-edge healthcare treatments is the ability to accurately capture patient anatomy in order to guide the manufacture of personalized prostheses. This article examines methods for capturing patient anatomy and discusses the degrees of personalization in medical manufacturing alongside a summary of current trends in scanning technology with a focus on identifying workflows for incorporating personalization into patient-specific products. Over the next decade, with increased harmonization of both personalization and automated prosthetic manufacturing will be the realization of improved patient compliance, satisfaction, and clinical outcomes.