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Clinical reading centers provide expertise for consistent, centralized analysis of medical data gathered in a distributed context. Accordingly, appropriate software solutions are required for the involved communication and data management processes. In this work, an analysis of general requirements and essential architectural and software design considerations for reading center information systems is provided. The identified patterns have been applied to the implementation of the reading center platform which is currently operated at the Center of Ophthalmology of the University Hospital of Tübingen.
We present an approach for segmenting individual cells and lamellipodia in epithelial cell clusters using fully convolutional neural networks. The method will set the basis for measuring cell cluster dynamics and expansion to improve the investigation of collective cell migration phenomena. The fully learning-based front-end avoids classical feature engineering, yet the network architecture needs to be designed carefully. Our network predicts how likely each pixel belongs to one of the classes and, thus, is able to segment the image. Besides characterizing segmentation performance, we discuss how the network will be further employed.
Background: Internationally, teledermatology has proven to be a viable alternative to conventional physical referrals. Travel cost and referral times are reduced while patient safety is preserved. Especially patients from rural areas benefit from this healthcare innovation. Despite these established facts and positive experiences from EU neighboring countries like the Netherlands or the United Kingdom, Germany has not yet implemented store-and-forward teledermatology in routine care.
Methods: The TeleDerm study will implement and evaluate store-and-forward teledermatology in 50 general practitioner (GP) practices as an alternative to conventional referrals. TeleDerm aims to confirm that the possibility of store-and-forward teledermatology in GP practices is going to lead to a 15% (n = 260) reduction in referrals in the intervention arm. The study uses a cluster-randomized controlled trial design. Randomization is planned for the cluster “county”. The main observational unit is the GP practice. Poisson distribution of referrals is assumed. The evaluation of secondary outcomes like acceptance, enablers and barriers uses a mixed methods design with questionnaires and interviews.
Discussion: Due to the heterogeneity of GP practice organization, patient management software, information technology service providers, GP personal technical affinity and training, we expect several challenges in implementing teledermatology in German GP routine care. Therefore, we plan to recruit 30% more GPs than required by the power calculation. The implementation design and accompanying evaluation is expected to deliver vital insights into the specifics of implementing telemedicine in German routine care.
Integrating tools and applications into a clinically useful system for individual continuous health data surveillance requires an architecture considering all relevant medical and technical conditions. Therefore, the requirements of an integrated system including a health app to collect and monitor sensor data to support personalized medicine are analyzed. The structure and behavior of the system are defined regarding the specific health use cases and scenarios. A vendor-independent architecture, which enables the collection of vital data from arbitrary wearables using a smartphone, is presented. The data is centrally managed and processed by attending physicians. The modular architecture allows the system to extend to new scenarios, data formats, etc. A prototypical implementation of the system shows the feasibility of the approach.
A clinically useful system for individual continuous health data monitoring needs an architecture that takes into account all relevant medical and technical conditions. The requirements for a health app to support such a system are collected, and a vendor independent architecture is designed that allows the collection of vital data from arbitrary wearables using a smartphone. A prototypical implementation for the main scenario shows the feasibility of the approach.
In this work, a web-based software architecture and framework for management and diagnosis of large amounts of medical data in an ophthalmologic reading center is proposed. Data management for multi-center studies requires merging of standing data and repeatedly gathered clinical evidence such as vital signs and raw data. If ophthalmologic questions are involved the data acquisition is often provided by non-medical staff at the point of care or a study center, whereas the medical finding is mostly provided by an ophthalmologist in a specialized reading center. The study data such as participants, cohorts and measured values are administrated at a single data center for the entire study. Since a specialized reading center maintains several studies, the medical staff must learn the different data administration for the different data center. With respect to the increasing number and sizes of clinical studies, two aspects must be considered. At first, an efficient software framework is required to support the data management, processing and diagnosis by medical experts at the reading center. In the second place, this software needs a standardized user-interface that has not to be trained/taylore /adapted for each new study. Furthermore different aspects of quality and security controls have to be included. Therefore, the objective of this work is to establish a multi purpose ophthalmologic reading center, which can be connected to different data centers via configurable data interfaces in order to treat various topics simultaneously.
The implementation of a web based portal QA solution will lead to a high acceptance of the staff as the usage of commonly known standard software (e.g. web browser) allows intuitive handling. In the daily use a significant simplification of the workflow and Performance enhancement can be achieved by easy access to the check documents. As the data is now saved in a database it can easily be processed and long-term trends can be displayed. Therefore possible errors can be detected much easier and earlier. By the usage of time stamps and user authentication procedures and user responsibilities are comprehensibly documented. As the software is browser based, integration into an existing software Environment is not critical. As only technical QA data is processed, no further data security measures are necessary. A certification as a medical product is not required.
Analysis of multicellular patterns is required to understand tissue organizational processes. By using a multi-scale object oriented image processing method, the spatial information of cells can be extracted automatically. Instead of manual segmentation or indirect measurements, such as general distribution of contrast or flow, the orientation and distribution of individual cells is extracted for quantitative analysis. Relevant objects are identified by feature queries and no low-level knowledge of image processing is required.
Continuous monitoring of individual vital parameters can provide information for the assessment of one’s health and indications of medical problems in the context of personalized medicine. Correlations between parameters and health issues are to be evaluated. As one project in this topic area, a telemedicine platform is implemented to gather data of outpatients via wearables and accumulate them for physicians and researchers to review. This work extracts requirements, draws use case scenarios, and shows the current system architecture consisting of a patient application, a physician application with a web server, and a backend server application. In further work, the prototype will assist to develop a vendor-free and open monitoring solution. A conclusion on functionality and usability will be evaluated in an imminent first study.
Mobile monitoring of outpatients during cancer therapy becomes possible through technological advancements. This study leveraged a new remote patient monitoring app for in-between systemic therapy sessions. Patients’ evaluation showed that the handling is feasible. Clinical implementation must consider an adaptive development cycle for reliable operations.
