Evidence map›Paper›PMID 39930273›Full record

ArticleMedical physics2025

Spectral performance for iodine quantification of a dual-source, dual-kV photon counting detector CT.

Tim Winfree, Kevin Treb, Cynthia McCollough, Shuai Leng

Abstract read
In one paragraph

Article in Medical physics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Quantitative PCCT spectral parameters for noninvasive prediction of EGFR status and its subtypes in lung adenocarcinoma.Cancer imaging : the official publication of the International Cancer Imaging Society · 2026
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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

4 authors.

Tim WinfreeDepartment of Radiology, Mayo Clinic, Rochester, Minnesota, USA.
Kevin TrebDepartment of Radiology, Mayo Clinic, Rochester, Minnesota, USA.
Cynthia McColloughDepartment of Radiology, Mayo Clinic, Rochester, Minnesota, USA.
Shuai LengDepartment of Radiology, Mayo Clinic, Rochester, Minnesota, USA.

Funding

Comprehensive characterization of coronary atherosclerotic disease using photon-counting-detector dual-source CT and its impact on patient managementR01EB028590 · NIBIB · MAYO CLINIC ROCHESTER · PI LENG, SHUAI, MCCOLLOUGH, CYNTHIA H · 2020 to 2023
$2.6M
NIBIB NIH HHS R01 EB028590NIH HHS R01 EB028590
6 · The paper itself

Abstract

backgroundMulti-energy CT (MECT) enables quantification of material concentrations by measuring linear attenuation coefficient line integrals with multiple x-ray spectra. Photon counting detector (PCD)-CT utilizes a detector-based approach for MECT that can suffer from substantial spectral overlap, resulting in amplified material quantification noise. Dual-source dual-kV approaches for MECT are currently utilized in some energy-integrating detector (EID)-CT systems and can potentially be utilized with PCD-CT for improved spectral separation. PURPOSE: To evaluate the iodine quantification performance of a novel dual-source (DS)-PCD-CT scan mode and compare to single-source (SS)-PCD-CT and DS-EID-CT. MATERIALS AND

methodsA 30 cm × 40 cm solid water phantom with four iodine inserts (2, 5, 10, and 15 mg/mL) was scanned with the three spectral modalities: SS-PCD-CT with two energy thresholds, DS-PCD-CT (90/Sn150 kV), and DS-EID-CT (90/Sn150 kV). For each modality, full-dose (12 mGy) and half-dose scans were acquired, and images were reconstructed with filtered back-projection using a quantitative (Qr40) kernel. When scanning in a DS configuration, the total radiation dose budget is split between two detectors, increasing the strength of a signal-dependent filter compared to a SS acquisition. To account for this effect, the modulation transfer function (MTF) for each modality was measured from a 0.05 mm tungsten wire. A linear spatial filter was applied to the SS images to match their MTF to that of the DS images. The resulting high- and low-energy images were input into an image-domain least squares material decomposition algorithm with iodine and water as the two basis materials. Iodine quantification accuracy and noise measured from the iodine basis images were used as figures of merit, and t-tests used to compare between modalities.

resultsThe 10% MTF cutoffs were 0.56, 0.57, 0.60, and 0.57 lp/mm for DS-EID-CT, DS-PCD-CT, SS-PCD-CT, and SS-PCD-CT after MTF-matching, respectively, with the SS-PCD-CT MTF cutoff dropping to 0.58 lp/mm at half-dose. Without accounting for the signal-dependent filter by matching the MTFs, the noise in iodine material basis images from SS-PCD-CT was 10% higher than that of DS-EID-CT. After matching the MTFs, the noise in the SS-PCD-CT iodine image was 9%-22% lower than that of the DS-EID-CT. The lowest iodine image noise was from the DS-PCD-CT, which was 39%-41% lower than the DS-EID-CT. The DS-PCD-CT noise magnitude was significantly different from the other modalities. Mean iodine quantification accuracy across all measured concentrations was within 5% for all modalities at full dose, but was only below 5% for the DS-PCD-CT at half-dose.

conclusionsSS-PCD-CT with two energy thresholds outperformed DS-EID-CT in terms of image noise in iodine basis images when spatial resolution was matched. DS-PCD-CT gave the lowest noise due to the combination of PCD technology and improved spectral separation from the different x-ray spectra.

Indexed as

IodinePhotonsTomography, X-Ray ComputedPhantoms, ImagingSignal-To-Noise RatioIodineadaptive filtrationdual‐source CTiodine quantificationmulti‐energy CTphoton counting detector CT

Identifiers

PMID39930273
PMCPMC12064377

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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.