Purpose: Myocardial blood flow (MBF) and myocardial flow reserve (MFR) are measurable by N-NH positron emission tomography (PET). MFR, which is the ratio of MBF under adenosine stress to MBF at rest, is prognostically valuable. The ASNC imaging guidelines/SNMMI procedure standards recommend using 2-3 mm pixels, and pixel size does differ between institutions. We sought to evaluate the effects of pixel sizes on the quantitative values calculated from N-NH PET images.
Methods: Thirty consecutive patients with ischemic heart disease who underwent N-NH PET were retrospectively enrolled. Dynamic images were quantified using PMOD's cardiac PET analysis tool (pixel sizes: 3.18, 2.03, and 1.59 mm). MBF under adenosine stress, MBF at rest, and MFR for the right coronary artery (RCA) region, left anterior descending artery region, and left circumflex coronary artery branch region innervation regions were calculated at each pixel size and compared.
Results: Quantitative values did not significantly differ according to pixel size in any of the regions. However, MFR values for the RCA fluctuated the most. Ischemic and non-ischemic regions remained visually discernible in qualitative images, with no variation in quantitative values, regardless of pixel size.
Conclusions: Quantitative values were not significantly affected by pixel sizes within the recommended range of 2-3 mm. Values for the RCA region may have been overestimated, but this was true for all pixel sizes.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1007/s10554-022-02639-3 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Advanced technologies in InGaN micro-LED fabrication to mitigate the sidewall effect.
Light Sci Appl
January 2025
Advanced Semiconductor Laboratory, Electrical and Computer Engineering Program, CEMSE Division, King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Kingdom of Saudi Arabia.
The size of InGaN micro-LEDs is continuously decreasing to meet the demands of various emerging applications, especially in tiny micro-displays such as AR/VR. However, the conventional pixel definition based on plasma etching significantly damages the mesa sidewalls, leading to a severe reduction in efficiency as the micro-LED size decreases. This seriously impedes the development and application of micro-LEDs.
View Article and Find Full Text PDFMulti-Person Localization Based on a Thermopile Array Sensor with Machine Learning and a Generative Data Model.
Sensors (Basel)
January 2025
Laboratory of Adaptive Lighting Systems and Visual Processing, Technical University of Darmstadt, Hochschulstr. 4a, 64289 Darmstadt, Germany.
Thermopile sensor arrays provide a sufficient counterbalance between person detection and localization while preserving privacy through low resolution. The latter is especially important in the context of smart building automation applications. Current research has shown that there are two machine learning-based algorithms that are particularly prominent for general object detection: You Only Look Once (YOLOv5) and Detection Transformer (DETR).
View Article and Find Full Text PDFBased on the Geometric Characteristics of Binocular Imaging for Yarn Remaining Detection.
Sensors (Basel)
January 2025
School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou 310018, China.
The automated detection of yarn margins is crucial for ensuring the continuity and quality of production in textile workshops. Traditional methods rely on workers visually inspecting the yarn margin to determine the timing of replacement; these methods fail to provide real-time data and cannot meet the precise scheduling requirements of modern production. The complex environmental conditions in textile workshops, combined with the cylindrical shape and repetitive textural features of yarn bobbins, limit the application of traditional visual solutions.
View Article and Find Full Text PDFBeam Tilt Aberration Detection of the Seven-Unit Phased Fiber Laser Array.
Micromachines (Basel)
December 2024
School of Optoelectronic Engineering, Changchun University of Science and Technology, Changchun 130022, China.
In this paper, we present a method based on the conjugate image principle and micro-nano optics to detect tilt aberrations of a phased fiber laser array system. A co-aperture optics system was adapted to detect the tilt aberrations of a seven-element phased fiber laser array system simultaneously. A Kepler telescope was designed to construct the conjugate relation between the exit pupil of a fiber optic laser array system and a microlens array and also to match the size of the seven beams and the microlens array.
View Article and Find Full Text PDFLightweightUNet: Multimodal Deep Learning with GAN-Augmented Imaging Data for Efficient Breast Cancer Detection.
Bioengineering (Basel)
January 2025
School of Chemical Engineering, Yeungnam University, Gyeongsan 38541, Republic of Korea.
Breast cancer ranks as the second most prevalent cancer globally and is the most frequently diagnosed cancer among women; therefore, early, automated, and precise detection is essential. Most AI-based techniques for breast cancer detection are complex and have high computational costs. Hence, to overcome this challenge, we have presented the innovative LightweightUNet hybrid deep learning (DL) classifier for the accurate classification of breast cancer.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!