The goal of this paper is to present a critical review of major Computer-Aided Detection systems (CADe) for lung cancer in order to identify challenges for future research. CADe systems must meet the following requirements: improve the performance of radiologists providing high sensitivity in the diagnosis, a low number of false positives (FP), have high processing speed, present high level of automation, low cost (of implementation, training, support and maintenance), the ability to detect different types and shapes of nodules, and software security assurance. The relevant literature related to “CADe for lung cancer” was obtained from PubMed, IEEEXplore and Science Direct database. Articles published from 2009 to 2013, and some articles previously published, were used. A systemic analysis was made on these articles and the results were summarized. Based on literature search, it was observed that many if not all systems described in this survey have the potential to be important in clinical practice. However, no significant improvement was observed in sensitivity, number of false positives, level of automation and ability to detect different types and shapes of nodules in the studied period. Challenges were presented for future research. Further research is needed to improve existing systems and propose new solutions. For this, we believe that collaborative efforts through the creation of open source software communities are necessary to develop a CADe system with all the requirements mentioned and with a short development cycle. In addition, future CADe systems should improve the level of automation, through integration with picture archiving and communication systems (PACS) and the electronic record of the patient, decrease the number of false positives, measure the evolution of tumors, evaluate the evolution of the oncological treatment, and its possible prognosis.

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Computer-aided detection system for lung cancer in computed tomography scans: Review and future prospects

Today, despite the advantages of the PACS system, its implementation in some healthcare organizations faces many challenges. One of the important factors in the successful implementation of a PACS system is identifying and prioritizing the challenges from the perspectives of involved staff and user of this system. Therefore, the aim of this study was to determine and compare the challenges of implementing PACS from perspectives these users in educational hospitals. This study was conducted on all IT and medical equipment staff, and radiology residents (n = 140) in Kerman University of Medical Sciences (KUMS) and Shiraz University of Medical Sciences (SUMS) in 2016. The data were collected through two researcher-made questionnaires. Their validity was approved by radiologists, IT staff, and medical informatics specialists and their reliability through calculation of Cronbach’s Alpha (0.969 and 0.795). We used Multivariate Analysis of Variance (MANOVA) to compare the scores given by three groups of participants in the challenges and Univariate Analysis of Variance (ANOVA) to compare the scores in two universities. The participants believed that technical challenges were more important than other challenges (x=3.74, SD = 0.7). IT experts (x=3.87, SD = 1) and radiology residents (x=3.95, SD = 0.9) gave the higher scores to the “shortage of high quality monitors” factor and medical equipment experts (x=4.26, SD = 0.87) to the “low speed of communication networks” factor among all technical challenges. The mean scores given to technical (x=76.1, SD = 13.5) and managerial (x=16, SD = 5.9) challenges in SUMS were more than the scores of the same challenges in KUMS (x=69.9, SD = 15.7) and (x=11.9, SD = 6.4) (p < 0.05). The technical challenges are the most common challenges to PACS implementation, and different universities experience different levels of technical challenges. Eliminating implementation challenges can reduce the risk of failure in the utilization process. Based on the results of this study, providing necessary infrastructures such as appropriate monitors and upgraded IT equipment can prevent many of the PACS implementation challenges.

Challenges of Implementing Picture Archiving and Communication System in Multiple Hospitals: Perspectives of Involved Staff and Users.

Imaging informatics professionals in New Zealand healthcare

The purpose of this paper is to propose a framework for cybersecurity risk management in telemedicine. The framework, which uses a bow-tie approach for medical image diagnosis sharing, allows the identification, analysis, and assessment of risks, considering the ISO/TS 13131:2014 recommendations. The bow-tie method combines fault tree analysis (FTA) and event tree analysis (ETA). The literature review supported the identification of the main causes and forms of control associated with cybersecurity risks in telemedicine. The main finding of this paper is that it is possible, through a structured model, to manage risks and avoid losses for everyone involved in the process of exchanging medical image information through telemedicine services. Through the framework, those responsible for the telemedicine services can identify potential risks in cybersecurity and act preventively, recognizing the causes even as, in a mitigating way, identifying viable controls and prioritizing investments. Despite the existence of many studies on cybersecurity, the paper provides theoretical contributions to studies on cybersecurity risks and features a new methodological approach, which incorporates both causes and consequences of the incident scenario.

/pdf/a-risk-assessment-framework-proposal-based-on-bow-tie-32ut2e9mvz.pdf

A Risk Assessment Framework Proposal Based on Bow-Tie Analysis for Medical Image Diagnosis Sharing within Telemedicine.

This research is dedicated to creating a data transformation and unification layer between a number of medical systems (which are essentially lab equipment such as CT, MRI, X-rays scanners and so on) and centralized data management system called PACS (picture archiving and communication system). Source data are present in different (even proprietary) formats and can't be fed to PACS as is.Another challenge is that the data provided by source medical information systems contain personal user information, so it needs to be anonymized prior to analysis. Authors of this paper created a methodology and a set of services to depersonalize, process, store and retrieve medical user data. The system tracks global user identifiers in depersonalized form, so it has the ability to group different samples related to the same user.The system retrieves the data from heterogeneous sources (namely, computer tomography storage, magnetic resonance imaging storage, X-rays storage, angiography storage and ultrasonic investigation storage), processes it using a predefined set of rules and transfers the data to the PACS. PACS allows computer scientists and engineers to perform research on depersonalised data and to generate a set of results. These results are stored in both depersonalized and personalized forms. They are fed to a special service which enriches them with personal user information and stores them in the medical system for a doctor to observe. Also, they are stored in the depersonalized form and can be presented to a general audience. A doctor validates the results of the research.Our research group is in charge of creating the new PACS service which can act as a proxy between the aforementioned medical systems and the old PACS. We are also developing our own DICOM storage (DICOM is an industrial standard of medical imaging information representation) as a backend to our PACS.

Dinesh Kapoor

Papers

Picture Archiving and Communication Systems (PACS) – A New Paradigm in Healthcare