Evidence map›Paper›PMID 40549181›Full record

ReviewAbdominal radiology (New York)2026

Assessment prior to liver tumor resection: what a radiologist needs to know.

Mahmoud Diab, Mindy X Wang, Aarya Ramprasad, Ann A Shi, Imran Ahmed, Sergio Klimkowski, Vincenzo K Wong, Khaled M Elsayes

Abstract readReview
PubMed Publisher
In one paragraph

Review in Abdominal radiology (New York), 2026. 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

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

1 citing paper in PubMed.

  1. Liver metastases beyond classical imaging findings.Abdominal radiology (New York) · 2026
    Review
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.

Mahmoud DiabThe University of Texas MD Anderson Cancer Center, Houston, USA.
Mindy X WangThe University of Texas MD Anderson Cancer Center, Houston, USA. mindywangmd@gmail.com.
Aarya RamprasadUniversity of Missouri-Kansas City, Kansas City, USA.
Ann A ShiThe University of Texas MD Anderson Cancer Center, Houston, USA.
Imran AhmedThe University of Texas MD Anderson Cancer Center, Houston, USA.
Sergio KlimkowskiThe University of Texas MD Anderson Cancer Center, Houston, USA.
Vincenzo K WongThe University of Texas MD Anderson Cancer Center, Houston, USA.
Khaled M ElsayesThe University of Texas MD Anderson Cancer Center, Houston, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Liver tumor resection remains the mainstay of treatment for patients with primary and secondary hepatic malignancies and can potentially be a curative option. With advances in surgical techniques, systemic therapies, and perioperative management, resectability criteria have expanded over time yet operative planning must still be carefully weighed between oncologic benefit and surgical risks along with residual liver function. While tumor detection is critical, radiologists also have an essential role in assessing tumor resectability, evaluating background liver disease, identifying surgically relevant vascular and biliary anatomy, and estimating future liver remnant adequacy. This review article aims to provide a practical guide for radiologists involved in the preoperative evaluation of patients with liver tumors. It highlights key surgical indications and contraindications for common hepatic malignancies, outlines essential preoperative imaging findings relevant to surgical planning and reviews the types of surgical resections.

Indexed as

HepatectomyLiver NeoplasmsPreoperative CareHumansAnatomic variationCholangiocarcinomaHepatectomyHepatocellular carcinomaNeoplasm metastasisRadiology

Identifiers

PMID40549181

What Socratic holds

Textmetadata
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 Socratic graph.