Evidence map›Paper›PMID 39925380›Full record

ArticleConference proceedings. International Conference on Image Formation in X-Ray Computed Tomography2024

Quantitative metal artifact reduction algorithm for spectral CT thermometry.

Leening P Liu, Kevin M Brown, Amy E Perkins, Michael C Soulen, Peter B Noël

Abstract read
In one paragraph

Article in Conference proceedings. International Conference on Image Formation in X-Ray Computed Tomography, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Dual-Layer Spectral CT for in Vivo Thermometry During Thermal Ablation.Cardiovascular and interventional radiology · 2026
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Leening P LiuDepartment of Bioengineering and Department of Radiology, Perelman School of Medicine, Philadelphia, PA, USA.
Kevin M BrownPhilips Healthcare, OH, USA.
Amy E PerkinsPhilips Healthcare, OH, USA.
Michael C SoulenDepartment of Radiology, Perelman School of Medicine, Philadelphia, PA, USA.
Peter B NoëlDepartment of Radiology, Perelman School of Medicine, Philadelphia, PA, USA.

Funding

Patient-specific, high-sensitivity spectral CT for assessment of pancreatic cancerR01EB030494 · NIBIB · UNIVERSITY OF PENNSYLVANIA · PI GANG, JIANAN GRACE, NOËL, PETER B · 2021 to 2024
$2.4M
NIBIB NIH HHS R01 EB030494
6 · The paper itself

Abstract

Spectral CT thermometry can non-invasively monitor internal temperatures to reduce local tumor recurrences caused by insufficient heating/treatment of the tumor and its surrounding safety margin. For its clinical translation, the applied metal artifact reduction algorithm requires quantitative accuracy to ensure the accuracy of generated temperature maps. The newly developed Spectrally Obtained Needle Artifact Reduction (SONAR) algorithm leverages the known shape of the applicator and spectral CT's material decomposition capabilities to isolate the applicator in projections. Projections with long path lengths through metal were then corrected by replacing them with modeled projections of an angled cylinder. To evaluate the accuracy of SONAR, a liver-mimicking phantom embedded with an ablation applicator and thermometers was scanned with a dual-layer spectral CT at phantom temperatures of 35 and 80 °C. Using spectral CT thermometry, temperature maps at 80 °C were generated for image slices with and without the applicator. SONAR significantly decreased streaks along the axis of the applicator. It also eliminated underestimated temperatures immediately adjacent to the applicator and overestimated temperatures in the periphery (2-3 cm from applicator). While application of SONAR resulted in minimal absolute difference in the temperature map without the applicator, averaging 1.1 ± 0.8 °C, temperatures decreased 7.0 ± 4.0 and 10.1 ± 2.3 °C at distances of 2-3 and 0.5-1 cm from the applicator, respectively, to better match the expected temperature. SONAR ultimately minimized metal artifacts and lessened overestimation of temperature in spectral CT thermometry maps. These quantitatively accurate maps will facilitate the

Indexed as

Metal Artifact ReductionSpectral CTThermometry

Identifiers

PMID39925380
PMCPMC11807397

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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.