Evidence map›Paper›PMID 39375653›Full record

ArticleBMC surgery2024

Prospective observational non-randomized trial protocol for surgical planner 3D image processing & reconstruction for locally advanced colon cancer.

Sebastián Jerí-McFarlane, Álvaro García-Granero, Gianluca Pellino, Noemi Torres-Marí, Aina Ochogavía-Seguí, Miguel Rodríguez-Velázquez, Margarita Gamundí-Cuesta, Francisco Xavier González-Argenté

Registry-linked trialAbstract readClinical Trial Protocol
In one paragraph

Article in BMC surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07528937 (Randomized Multicenter Study Protocol), which is not on this map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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.

NCT07528937 nanot yet recruitingnot on this mapstarted 2026, after this paper: background citation

Randomized Multicenter Study Protocol: Application of 3D Reconstruction for Preoperative Strategy of Locally Advanced Colon Cancer

TypeinterventionalSponsorFundació d'investigació Sanitària de les Illes BalearsRan2026 to 2031Enrolled168ConditionsColon Neoplasms, Locally Advanced Colon Cancer, 3D ReconstructionArms3D reconstruction
3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

8 authors.

Sebastián Jerí-McFarlaneColorectal Unit, General & Digestive Surgery Department, Hospital Universitario Son Espases, Palma, Spain.
Álvaro García-GraneroColorectal Unit, General & Digestive Surgery Department, Hospital Universitario Son Espases, Palma, Spain. alvarogggf@hotmail.com.
Gianluca PellinoDepartment of Advanced Medical and Surgical Sciences, Università Degli Studi Della Campania "Luigi Vanvitelli", Naples, Italy.
Noemi Torres-MaríColorectal Unit, General & Digestive Surgery Department, Hospital Universitario Son Espases, Palma, Spain.
Aina Ochogavía-SeguíColorectal Unit, General & Digestive Surgery Department, Hospital Universitario Son Espases, Palma, Spain.
Miguel Rodríguez-VelázquezInnovation and Technology Department, Cella Medical Solutions, Murcia, Spain.
Margarita Gamundí-CuestaColorectal Unit, General & Digestive Surgery Department, Hospital Universitario Son Espases, Palma, Spain.
Francisco Xavier González-ArgentéColorectal Unit, General & Digestive Surgery Department, Hospital Universitario Son Espases, Palma, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionColon cancer presents significant surgical challenges that necessitate the development of precise strategies. Standardization with complete mesocolic excision (CME) is common, but some cases require extended resections. This study investigates the use of 3D Image Processing and Reconstruction (3D-IPR) to improve diagnostic accuracy in locally advanced colon cancer (LACC) with suspected infiltration and achieve R0 surgery.

methodsSingle-center, prospective, observational, comparative, non-randomized study. •Participants: Patients aged > 18 years undergoing LACC surgery, as indicated by CT scans, confirmed via colonoscopy. Exclusion criteria include neoadjuvant therapy, suspected carcinomatosis on CT, and unresectable tumors. •Interventions: 3D-IPR models are used for surgical planning, providing detailed tumor and surrounding structure metrics. Surgical procedures are guided by CT scans and intraoperative findings, categorized by surgical margins as R0, R1, or R2. •Objective: The primary goal is to evaluate 3D-IPR's utility in achieving R0 resection in LACC with suspected infiltration. Secondary objectives include assessing preoperative surgical strategy, comparing CT reports, detecting adenopathy, and identifying vascularization and anatomical variants. • Outcome: The main outcome is the diagnostic accuracy of 3D-IPR in determining tumor infiltration of neighboring structures compared to conventional CT scans, using definitive pathological reports as the gold standard.

results•Recruitment and Number Analyzed: The study aims to recruit about 20 patients annually over two years, focusing on preoperative 3D-IPR analysis and subsequent surgical procedures. •Outcome Parameters: These include loco-regional and distant recurrence rates, peritoneal carcinomatosis, disease-free and overall survival, and mortality due to oncologic progression. •Harms: No additional risks from CT scans, as they are mandatory for staging colon tumors. 3D-IPR is derived from these CT scans. DISCUSSION: If successful, this study could provide an objective tool for precise tumor extension delimitation, aiding decision-making for radiologists, surgeons, and multidisciplinary teams. Enhanced staging through 3D-IPR may influence therapeutic strategies, reduce postsurgical complications, and improve the quality of life of patients with LACC.

trial registrationTrial is registered at ISRCTN registry as ISRCTN81005215. Protocol version I (Date 29/06/2023).

Indexed as

Colonic NeoplasmsImaging, Three-DimensionalColectomyHumansNeoplasm StagingNon-Randomized Controlled Trials as TopicObservational Studies as TopicProspective StudiesTomography, X-Ray Computed3D ReconstructionColon neoplasmColorectal surgeryInnovation

Identifiers

PMID39375653
PMCPMC11457321

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Registered trials

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.