Dual sideband receiver for radio-over-fiber.

A dual sideband reception scheme for radio-over fiber (RoF) links is introduced. It is shown that the new receiver can increase the performance of noise-limited systems by up to 3 dB (2.97 dB in a lab back-to-back experiment). The receiver scheme exploits the fact that current RoF links do not realize their full potential. This is because in typical RoF receivers, the radio-frequency (RF) signals are mapped back to the optical domain by means of electro-optical modulator. In this process energy typically is lost as only one of the two generated sidebands is subsequently used. The suggested receiver exploits the signal of both sidebands. The receiver scheme was subsequently tested in a full optical-RF-optical transmission link at RF carrier frequencies of 228 GHz over a free-space channel spanning distances of 1400 m for symbol rates of up to 48 Gbaud 4 QAM. Here, we could achieve SNR improvements of up to 2.6 dB.

Correction: The BioRef Infrastructure, a Framework for Real-Time, Federated, Privacy-Preserving, and Personalized Reference Intervals: Design, Development, and Application.

[This corrects the article DOI: 10.2196/47254.].

The BioRef Infrastructure, a Framework for Real-Time, Federated, Privacy-Preserving, and Personalized Reference Intervals: Design, Development, and Application.

BACKGROUND: Reference intervals (RIs) for patient test results are in standard use across many medical disciplines, allowing physicians to identify measurements indicating potentially pathological states with relative ease. The process of inferring cohort-specific RIs is, however, often ignored because of the high costs and cumbersome efforts associated with it. Sophisticated analysis tools are required to automatically infer relevant and locally specific RIs directly from routine laboratory data. These tools would effectively connect clinical laboratory databases to physicians and provide personalized target ranges for the respective cohort population. OBJECTIVE: This study aims to describe the BioRef infrastructure, a multicentric governance and IT framework for the estimation and assessment of patient group-specific RIs from routine clinical laboratory data using an innovative decentralized data-sharing approach and a sophisticated, clinically oriented graphical user interface for data analysis. METHODS: A common governance agreement and interoperability standards have been established, allowing the harmonization of multidimensional laboratory measurements from multiple clinical databases into a unified "big data" resource. International coding systems, such as the International Classification of Diseases, Tenth Revision (ICD-10); unique identifiers for medical devices from the Global Unique Device Identification Database; type identifiers from the Global Medical Device Nomenclature; and a universal transfer logic, such as the Resource Description Framework (RDF), are used to align the routine laboratory data of each data provider for use within the BioRef framework. With a decentralized data-sharing approach, the BioRef data can be evaluated by end users from each cohort site following a strict "no copy, no move" principle, that is, only data aggregates for the intercohort analysis of target ranges are exchanged. RESULTS: The TI4Health distributed and secure analytics system was used to implement the proposed federated and privacy-preserving approach and comply with the limitations applied to sensitive patient data. Under the BioRef interoperability consensus, clinical partners enable the computation of RIs via the TI4Health graphical user interface for query without exposing the underlying raw data. The interface was developed for use by physicians and clinical laboratory specialists and allows intuitive and interactive data stratification by patient factors (age, sex, and personal medical history) as well as laboratory analysis determinants (device, analyzer, and test kit identifier). This consolidated effort enables the creation of extremely detailed and patient group-specific queries, allowing the generation of individualized, covariate-adjusted RIs on the fly. CONCLUSIONS: With the BioRef-TI4Health infrastructure, a framework for clinical physicians and researchers to define precise RIs immediately in a convenient, privacy-preserving, and reproducible manner has been implemented, promoting a vital part of practicing precision medicine while streamlining compliance and avoiding transfers of raw patient data. This new approach can provide a crucial update on RIs and improve patient care for personalized medicine.

Tbit/s line-rate satellite feeder links enabled by coherent modulation and full-adaptive optics.

Free-space optical (FSO) communication technologies constitute a solution to cope with the bandwidth demand of future satellite-ground networks. They may overcome the RF bottleneck and attain data rates in the order of Tbit/s with only a handful of ground stations. Here, we demonstrate single-carrier Tbit/s line-rate transmission over a free-space channel of 53.42 km between the Jungfraujoch mountain top (3700 m) in the Swiss Alps and the Zimmerwald Observatory (895 m) near the city of Bern, achieving net-rates of up to 0.94 Tbit/s. With this scenario a satellite-ground feeder link is mimicked under turbulent conditions. Despite adverse conditions high throughput was achieved by employing a full adaptive optics system to correct the distorted wavefront of the channel and by using polarization-multiplexed high-order complex modulation formats. It was found that adaptive optics does not distort the reception of coherent modulation formats. Also, we introduce constellation modulation - a new four-dimensional BPSK (4D-BPSK) modulation format as a technique to transmit high data rates under lowest SNR. This way we show 53 km FSO transmission of 13.3 Gbit/s and 210 Gbit/s with as little as 4.3 and 7.8 photons per bit, respectively, at a bit-error ratio of 1 ∙ 10-3. The experiments show that advanced coherent modulation coding in combination with full adaptive optical filtering are proper means to make next-generation Tbit/s satellite communications practical.

Big Data in Laboratory Medicine-FAIR Quality for AI?

Laboratory medicine is a digital science. Every large hospital produces a wealth of data each day-from simple numerical results from, e.g., sodium measurements to highly complex output of "-omics" analyses, as well as quality control results and metadata. Processing, connecting, storing, and ordering extensive parts of these individual data requires Big Data techniques. Whereas novel technologies such as artificial intelligence and machine learning have exciting application for the augmentation of laboratory medicine, the Big Data concept remains fundamental for any sophisticated data analysis in large databases. To make laboratory medicine data optimally usable for clinical and research purposes, they need to be FAIR: findable, accessible, interoperable, and reusable. This can be achieved, for example, by automated recording, connection of devices, efficient ETL (Extract, Transform, Load) processes, careful data governance, and modern data security solutions. Enriched with clinical data, laboratory medicine data allow a gain in pathophysiological insights, can improve patient care, or can be used to develop reference intervals for diagnostic purposes. Nevertheless, Big Data in laboratory medicine do not come without challenges: the growing number of analyses and data derived from them is a demanding task to be taken care of. Laboratory medicine experts are and will be needed to drive this development, take an active role in the ongoing digitalization, and provide guidance for their clinical colleagues engaging with the laboratory data in research.

Software-Based Evaluation of Optimization Potential for Clinical MRI Scanners in Radiology. / Software-basierte Evaluation des Optimierungspotenzials bei klinischen MRT-Scannern in der Radiologie.

OBJECTIVE: The aim of the study was to use a software application to analyze the examination times and changeover times of two clinically highly applied MRI scanners at a university hospital for radiology and to evaluate whether this could result in optimization potential for examination planning in the daily clinical routine of MRI diagnostics. MATERIALS AND METHODS: Based on the newly developed software application "Teamplay Usage" (Siemens Healthineers, Germany), the examinations carried out on two MRI scanners (1.5 T and 3 T) were investigated within an analysis period of 12 months with regard to the type of examination and its duration. In addition, compliance with the previously defined planning time (30, 45, 60 min.) was checked and deviations were analyzed. In addition, the changeover times between the examinations were determined and a possible influence due to the exchange of MRI coils was investigated for a selection of change combinations. RESULTS: For the total of 7184 (1.5 T: 3740; 3 T: 3444) examinations included in the study, the median examination time was 43:02 minutes (1.5 T: 43:17 min.; 3 T: 42:45 min.). The ten most frequent types of examinations per MRI scanner were completed within the predefined plan time of 54.5 % (1.5 T) and 51.9 % (3 T), taking into account a previously defined preparation and post-processing time of 9 minutes per examination. Overall, more time was spent on examinations with a planned time of 30 minutes, whereas the majority of the examinations planned with 45 minutes were also completed within this time. Examinations with a planned time of 60 minutes usually took less time. A comparison between the planned time and the determined examination duration of the most common types of examinations showed overall a slight potential for optimization. Coil exchanges between two examinations had a small, but statistically not significant effect on the median changeover time (p = 0.062). CONCLUSION: Utilizing a software-based analysis, a detailed overview of the type of examination, examination duration, and changeover times of frequently used clinical MRI scanners could be obtained. In the clinic examined, there was little potential for optimization of examination planning. An exchange of MRI coils necessary for different types of examination only had a small effect on the changeover times. KEY POINTS: · The use of the "Teamplay Usage" software application enables a comprehensive overview of the type of examination, examination duration, and changeover times for MRI scanners.. · Adjustments to examination planning for MRI diagnostics show optimization potential, which, however, is to be assessed as low in the clinic examined.. · Necessary replacements of MRI coils only have a small effect on the changeover times.. CITATION FORMAT: · Meyl TP, Berghöfer A, Blatter T et al. Software-Based Evaluation of Optimization Potential for Clinical MRI Scanners in Radiology. Fortschr Röntgenstr 2022; 194: 391 - 399.