Adjustment of vascular 2-deoxy-2-[18F]fluoro-d-glucose uptake values over time through a modeling approach

To develop and test a model predicting 2-deoxy-2-[18F]fluoro-d-glucose ([18F]FDG) standardized uptake value (SUV) changes over time in the aorta and the superior vena cava (SVC). Maximum aortic SUV and mean SVC SUV were determined at two time points (T1 and T2) in the ascending (ASC), descending (DSC), abdominal (ABD) aorta, aortic arch (ARC) and SVC of patients who have undergone [18F]FDG PET/CT for clinical purposes. For SUV prediction at T2, linear and non-linear models of SUV difference for a given time change were developed in a derivation group. The results were tested in an independent validation group, whilst model reproducibility was tested in patients of the validation group who have undergone a second clinically indicated scan. Applying the linear model in the derivation group, there were no statistically significant differences in measurements obtained in the examined segments: mean differences ranged from 0 ± 0.10 in SVC to 0.01 ± 0.13 in ARC between measured and predicted SUV. In contrast, in the non-linear model, there were statistically significant differences in measurements, except in ARC, with mean differences ranging from 0.04 ± 0.14 in ARC to 0.28 ± 0.13 in ABD. In the validation group using the linear model, there were no statistically significant differences, with mean differences ranging from − 0.01 ± 0.08 in ASC to − 0.03 ± 0.11 in ABD. Regarding reproducibility, mean differences were no statistically significant, ranging from 0.004 ± 0.06 in ASC to − 0.02 ± 0.16 in ABD. We have developed a linear model allowing accurate and reproducible prediction of SUV changes over time in the aorta and SVC. © 2019, Springer Nature B.V

Design and characterization of the I-ImaS multi-element X-ray detector system

I-ImaS (Intelligent Imaging Sensors) is a European project aiming to produce new, intelligent x-ray imaging systems using novel APS sensors to create optimal diagnostic images. Initial systems have been constructed for medical imaging; specifically mammography and dental encephalography. However, the I-ImaS system concept could be applied to all areas of x-ray imaging, including homeland security and industrial QA. The I-ImaS system intelligence is implemented by the use of APS technology and FPGAs, allowing real-time analysis of data during image acquisition. This gives the system the capability to perform as an on-the-fly adaptive imaging system, with the potential to create images with maximum diagnostic information within given dose constraints. The I-ImaS system uses a scanning linear array of scintillatorcoupled 1.5-D CMOS Active Pixel Sensors to create a full 2-D x-ray image of an object. This paper describes the parameters considered when choosing the scintillator elements of the detectors. A study of the positioning of the sensors to form a linear detector is also considered, along with a discussion of the potential losses in image quality associated with creating a linear sensor by tiling many smaller sensors. Preliminary results show that the detectors have sufficient performance to be used successfully in the initial mammographie and encephalographic I-ImaS systems that are currently under construction. © 2008 IEEE

I-IMAS: A 1.5D sensor for high-resolution scanning

We have developed a 1.5 D CMOS active pixel sensor to be used in conjunction with a scintillator for X-ray imaging. Within the Intelligent Imaging Sensors (I-ImaS) project, multiple sensors will be aligned to form a line-scanning system and its performance evaluated with respect to existing sensors in other digital radiography systems. Each sensor contains a 512×32 array of pixels and the electronics to convert the collected amount of charge to a digital output value. These include programmable gain amplifiers (PGAs) and analogue-to-digital converters (ADCs). The gain of the PGA can be switched between one or two, to increase the sensitivity for smaller collected charge; the ADC is a 14-bit successive approximation with a sampling rate of 1.25 MHz. The ASIC includes a programmable column fixed pattern noise mitigation circuit and a digitally controllable pixel reset mode block. Here we will describe the sensor design and the expected performance. © 2006 Elsevier B.V. All rights reserved

Adaptive image content-based exposure control for scanning applications in radiography

I-ImaS (Intelligent Imaging Sensors) is a European project which has designed and developed a new adaptive X-ray imaging system using on-line exposure control, to create locally optimized images. The I-ImaS system allows for real-time image analysis during acquisition, thus enabling real-time exposure adjustment. This adaptive imaging system has the potential of creating images with optimal information within a given dose constraint and to acquire optimally exposed images of objects with variable density during one scan. In this paper we present the control system and results from initial tests on mammographic and encephalographic images. Furthermore, algorithms for visualization of the resulting images, consisting of unevenly exposed image regions, are developed and tested. The preliminary results show that the same image quality can be achieved at 30-70% lower dose using the I-ImaS system compared to conventional mammography systems. © Springer-Verlag Berlin Heidelberg 2007

A scanning system for intelligent imaging: I-ImaS.

27nonenoneLONGO R.; A. ASIMIDIS; D. CAVOURAS; C. ESBRAND; A. FANT; P. GASIOREK; H. GEORGIOU; G. HALL; J. JONES; J. LEAVER; G. LI; J. GRIFFITHS; D. MACHIN; N. MANTHOS; M. METAXAS; M. NOY; J. M. STBY; F. PSOMADELLIS; T. ROKVIC; G. ROYLE; H. SCHULERUD; R. SPELLER; PF. VAN DER STELT; S. THEODORIDIS; F. TRIANTIS; R. TURCHETTA; C. VENANZILongo, Renata; A., Asimidis; D., Cavouras; C., Esbrand; A., Fant; P., Gasiorek; H., Georgiou; G., Hall; J., Jones; J., Leaver; G., Li; J., Griffiths; D., Machin; N., Manthos; M., Metaxas; M., Noy; J. M., Stby; F., Psomadellis; T., Rokvic; G., Royle; H., Schulerud; R., Speller; VAN DER STELT, P. F.; S., Theodoridis; F., Triantis; R., Turchetta; C., Venanz