ArticleJournal of magnetic resonance (San Diego, Calif. : 1997)2015
3D pulse EPR imaging from sparse-view projections via constrained, total variation minimization.
Article in Journal of magnetic resonance (San Diego, Calif. : 1997), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 27 citations in OpenAlex.
- HDTV: a high-order directional total variation reconstruction algorithm from sparse and limited-angle data in electron paramagnetic resonance imaging.Quantitative imaging in medicine and surgery · 2025Article
- Partial Acquisition of Spectral Projections Accelerates Four-dimensional Spectral-spatial EPR Imaging for Mouse Tumor Models: A Feasibility Study.Molecular imaging and biology · 2024Article
- Directional TV algorithm for fast EPR imaging.Journal of magnetic resonance (San Diego, Calif. : 1997) · 2024Article
- An iterative reconstruction algorithm without system matrix for EPR imaging.Journal of magnetic resonance (San Diego, Calif. : 1997) · 2022Article
- A balanced total-variation-Chambolle-Pock algorithm for EPR imaging.Journal of magnetic resonance (San Diego, Calif. : 1997) · 2021Article
- Algebraic reconstruction of 3D spatial EPR images from high numbers of noisy projections: An improved image reconstruction technique for high resolution fast scan EPR imaging.Journal of magnetic resonance (San Diego, Calif. : 1997) · 2020Article
- EPR Oximetry Sensor-Developing a TAM Derivative for In Vivo Studies.Cell biochemistry and biophysics · 2018Article
- Accelerated dynamic EPR imaging using fast acquisition and compressive recovery.Journal of magnetic resonance (San Diego, Calif. : 1997) · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
Abstract
Tumors and tumor portions with low oxygen concentrations (pO2) have been shown to be resistant to radiation therapy. As such, radiation therapy efficacy may be enhanced if delivered radiation dose is tailored based on the spatial distribution of pO2 within the tumor. A technique for accurate imaging of tumor oxygenation is critically important to guide radiation treatment that accounts for the effects of local pO2. Electron paramagnetic resonance imaging (EPRI) has been considered one of the leading methods for quantitatively imaging pO2 within tumors in vivo. However, current EPRI techniques require relatively long imaging times. Reducing the number of projection scan considerably reduce the imaging time. Conventional image reconstruction algorithms, such as filtered back projection (FBP), may produce severe artifacts in images reconstructed from sparse-view projections. This can lower the utility of these reconstructed images. In this work, an optimization based image reconstruction algorithm using constrained, total variation (TV) minimization, subject to data consistency, is developed and evaluated. The algorithm was evaluated using simulated phantom, physical phantom and pre-clinical EPRI data. The TV algorithm is compared with FBP using subjective and objective metrics. The results demonstrate the merits of the proposed reconstruction algorithm.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.