Evidence map›Paper›PMID 39276190›Full record

ArticleAbdominal radiology (New York)2025

Achieving sub-millisievert CT colonography for accurate colorectal tumor detection using smart examination protocols: a prospective self-controlled study.

Jingyi Zhang, Mengting Hu, Qiye Cheng, Shigeng Wang, Yijun Liu, Yujing Zhou, Jianying Li, Wei Wei

Abstract read
In one paragraph

Article in Abdominal radiology (New York), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Jingyi ZhangFirst Affiliated Hospital of Dalian Medical University, Dalian, China.
Mengting HuFirst Affiliated Hospital of Dalian Medical University, Dalian, China.
Qiye ChengFirst Affiliated Hospital of Dalian Medical University, Dalian, China.
Shigeng WangFirst Affiliated Hospital of Dalian Medical University, Dalian, China.
Yijun LiuFirst Affiliated Hospital of Dalian Medical University, Dalian, China.
Yujing ZhouFirst Affiliated Hospital of Dalian Medical University, Dalian, China.
Jianying LiCT Research, GE Healthcare, Dalian, Dalian, China.
Wei WeiFirst Affiliated Hospital of Dalian Medical University, Dalian, China. weiweidy1988@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo assess the feasibility of combining Auto-kVp selection technique, higher preset ASIR-V and noise index (NI) to realize individualized sub-mSv CT colonography (CTC) for accurate colorectal tumor detection and localization.

methodsNinety patients with suspected colorectal cancer (CRC) were prospectively enrolled to undergo standard dose CTC (SDCTC) in the prone and ultra-low dose CTC (ULDCTC) in the supine position. SDCTC used 120 kVp, preset ASIR-V of 30%, SmartmA for a NI of 13; ULDCTC used Auto-kVp selection technique with 80 or 100 kVp, preset ASIR-V of 60%, SmartmA for a NI of 13 for 80 kVp, and NI of 15 for 100 kVp. The effective dose (ED), image quality [signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of colorectal neoplasms] between the two protocols were compared and the accuracies of tumor locations were evaluated for CTC in comparison with the surgery results.

resultsThe mean ED of the ULDCTC-80 kVp subgroup was 0.70 mSv, 71.43% lower than the 2.45 mSv for the 120 kVp group, while that of the ULDCTC-100 kVp subgroup was 0.98 mSv, 73.00% lower than the 3.63 mSv for the 120 kVp group (P < 0.001). The tumor SNR and CNR of the ULDCTC were higher than those of SDCTC (P < 0.05), while there was no difference in the subjective image quality between them with good inter-observer agreement (Kappa: 0.805-0.923). Both SDCTC and ULDCTC groups had high detection rate of colorectal tumors, along with good consistency in determining tumor location compared with surgery reports (Kappa: 0.718-0.989).

conclusionThe combination of Auto-kVp selection, higher preset ASIR-V and NI achieves individualized sub-mSv CTC with good performance in detecting and locating CRC with surgery and consistent results between SDCTC and ULDCTC.

Indexed as

Colonography, Computed TomographicColorectal NeoplasmsAdultAgedAged, 80 and overContrast MediaFeasibility StudiesFemaleHumansMaleMiddle AgedProspective StudiesRadiation DosageSignal-To-Noise RatioContrast MediaColonography, computed tomographicColorectal neoplasmsImage reconstructionRadiation dosage

Identifiers

PMID39276190
PMCPMC11821708

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.