Evidence map›Paper›PMID 37894475›Full record

ArticleCancers2023

Defining MRI Superiority over CT for Colorectal and Neuroendocrine Liver Metastases.

Marc A Attiyeh, Gautam K Malhotra, Daneng Li, Saro B Manoukian, Pejman M Motarjem, Gagandeep Singh

Open access · goldAbstract read
In one paragraph

Article in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.1field-weighted citation impact, top 21% of its field
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

4 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Article
  3. Observational
  4. 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

6 authors at 3 institutions in 1 country.

Marc A AttiyehDepartment of Surgical Oncology, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.ORCID 0000-0002-9949-1449
Gautam K MalhotraDepartment of Surgery, USC, Keck School of Medicine, Los Angeles, CA 90033, USA.ORCID 0000-0003-4563-0172
Daneng LiDepartment of Medical Oncology, City of Hope National Medical Center, Duarte, CA 91010, USA.ORCID 0000-0001-5330-7522
Saro B ManoukianDepartment of Radiology, City of Hope National Medical Center, Duarte, CA 91010, USA.
Pejman M MotarjemDepartment of Radiology, City of Hope National Medical Center, Duarte, CA 91010, USA.
Gagandeep SinghDepartment of Surgery, City of Hope National Medical Center, Duarte, CA 91010, USA.
City Of Hope National Medical Center · USCedars-Sinai Medical Center · USKeck Hospital of USC · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWe compared CT and MRI for staging metastatic colorectal or neuroendocrine liver metastases (CRLMs and NELMs, respectively) to assess their impact on tumor burden.

methodsA prospectively maintained database was queried for patients who underwent both imaging modalities within 3 months, with two blinded radiologists (R1 and R2) independently assessing the images for liver lesions. To minimize recall bias, studies were grouped by modality, and were randomized and evaluated separately.

resultsOur query yielded 76 patients (42 CRLMs; 34 NELMs) with low interrater variability (intraclass correlation coefficients: CT = 0.941, MRI = 0.975). For CRLMs, there were no significant differences in lesion number or size between CT and MRI. However, in NELMs, Eovist

conclusionsCT and MRI are equivalent for CRLMs, but for NELMs, MRI outperforms CT in detecting more and smaller lesions, potentially influencing treatment planning and surgery.

Indexed as

colorectal liver metastasesCTEovistimagingMRIneuroendocrine liver metastasesstagingsurgery

Identifiers

PMID37894475
PMCPMC10605771
OpenAlexW4387878860

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.