PubMed Health⌕ Search

PubMed · 6611390

Improved SPECT quantification using compensation for scattered photons.

Abstract

SPECT images are degraded by the inclusion of Compton-scattered photons within the pulse-height window. Phantom and patient studies with Tc-99m were used to evaluate a compensation method that consists of subtracting a fraction of the image reconstructed using events recorded within a secondary pulse-height window (92-125 keV) from that derived from the photopeak pulse-height window (127-153 keV). Images of line sources in air and in a water-filled phantom were stored. The compensated line spread functions (LSFs) were evaluated. In water, the absolute counting rates for the SPECT LSFs were within 10% of the rates measured in air. The phantom consisted of six solid acrylic spheres (diameters 10, 13, 16, 19, 25, 32 mm) placed within a cylindrical (22 cm diam) distribution of Tc-99m. For sphere diameters greater than 25 mm, the measured image contrasts were within 8% of the true uptake ratios. Our results have shown that high-quality, camera-based SPECT systems can reconstruct artifact-free images by making additional use of projection data acquired in a pulse-height window other than that over the primary photopeak. This compensation method results in qualitative and quantitative improvements for the limited source geometries investigated. Further studies are required to optimize this heuristic approach for other source geometries.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

R J Jaszczak, K L Greer, C E Floyd, C C Harris, R E Coleman. 1984. Improved SPECT quantification using compensation for scattered photons.. https://pubmed.ncbi.nlm.nih.gov/6611390/

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Global Genomic Surveillance.

Global genomic surveillance has emerged as a foundational pillar of public health in the twenty-first century, enabling real-time tracking of pathogen evolution and informing outbreak response. This chapter examines the strategic architecture of global genomic surveillance, focusing on its application to arboviruses such as chikungunya virus (CHIKV). It explores the integration of genomic data with epidemiological, clinical, and environmental information within a One Health framework, while addressing critical challenges in governance, equity, and interoperability. The discussion covers the entire genomic surveillance workflow, from sample collection and sequencing to bioinformatic analysis and phylogenetic inference, and highlights the transformative role of artificial intelligence (AI) in predictive surveillance. By analyzing global initiatives, operational barriers, and emerging technologies, this chapter underscores the necessity of sustainable, equitable, and interoperable genomic systems to proactively address current and future infectious disease threats.

Humans↗

Systematic Dissection of Key Driver Perturbation Signatures in Single Cells via ECCITE-seq.

CRISPR screens, such as expanded CRISPR-compatible cellular indexing of transcriptomes and epitopes by sequencing (ECCITE-seq), enable the simultaneous measurement of transcriptomes, gRNA identity, and cell-surface protein expression at single-cell resolution to systematically interrogate gene function. This platform provides a powerful and scalable experimental approach for validating disease-associated regulators identified by large-scale association studies and other computational methods, including network-based analyses of multi-omics data. Here, as an example application, we describe an ECCITE-seq framework to characterize the transcriptomic consequences of perturbing multiple neuronal key driver genes associated with Alzheimer's disease (AD) in human-induced pluripotent stem cell (hiPSC)-derived neurons. More broadly, by integrating customized pooled gRNA libraries with different CRISPR effectors across multiple cell types, this approach allows for the assessment of the regulatory impact of candidate genes implicated in development and disease processes.

Humans↗

Identification of Genome-Wide Chromatin Structural Aberration in Cancer by Hi-C Analysis.

Aberrant three-dimensional genome organization is a hallmark of cancer, often driving oncogene activation through mechanisms such as enhancer hijacking. High-throughput chromosome conformation capture (Hi-C) maps these interactions on a genome-wide scale. Unlike earlier dilution-based methods, in situ Hi-C performs proximity ligation within intact nuclei, minimizing random ligation noise and enabling fine-scale structure detection. This chapter describes an optimized in situ Hi-C protocol tailored for cancer cell lines using MboI digestion and biotin-mediated pull-down to generate high-complexity libraries. We further outline a computational workflow that extends beyond standard topological mapping of compartments and topologically associating domains to identify cancer-specific aberrations. Specifically, we focus on detecting chromosomal rearrangements (structural variants) and characterizing the distinct circular topology of extrachromosomal DNA. This integrated experimental and analytical framework provides the necessary tools to dissect the spatial dysregulation underlying tumor evolution.

Humans↗