Evidence map›Paper›PMID 39404938›Full record

Observational studyJournal of neuro-oncology2025

DTI fiber-tracking parameters adjacent to gliomas: the role of tract irregularity value in operative planning, resection, and outcome.

Daniele Armocida, Andrea Bianconi, Giuseppa Zancana, Tingting Jiang, Alessandro Pesce, Fulvio Tartara, Diego Garbossa, Maurizio Salvati, Antonio Santoro, Carlo Serra and 1 more

Abstract readObservational Study
In one paragraph

Observational study in Journal of neuro-oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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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

11 authors.

Daniele ArmocidaDepartment of Neuroscience "Rita Levi Montalcini", Neurosurgery Unit, University of Turin, Via Cherasco 15, Turin (TO), 10126, Italy. danielearmocida@yahoo.it.
Andrea BianconiDepartment of Neuroscience "Rita Levi Montalcini", Neurosurgery Unit, University of Turin, Via Cherasco 15, Turin (TO), 10126, Italy.
Giuseppa ZancanaHuman Neurosciences Department Neurosurgery Division, "La Sapienza" University, Policlinico Umberto 6 I, viale del Policlinico 155, Rome (RM), 00161, Italy.
Tingting JiangHuman Neurosciences Department Neurosurgery Division, "La Sapienza" University, Policlinico Umberto 6 I, viale del Policlinico 155, Rome (RM), 00161, Italy.
Alessandro PesceNeurosurgery Unit, Università degli studi di Roma (Tor Vergata), Policlinico Tor Vergata (PTV), Viale Oxford, 81, 00133, Rome (RM), Italy.
Fulvio TartaraUnit of Neurosurgery, Istituto Clinico Città Studi, Milan, Italy.
Diego GarbossaDepartment of Neuroscience "Rita Levi Montalcini", Neurosurgery Unit, University of Turin, Via Cherasco 15, Turin (TO), 10126, Italy.
Maurizio SalvatiNeurosurgery Unit, Università degli studi di Roma (Tor Vergata), Policlinico Tor Vergata (PTV), Viale Oxford, 81, 00133, Rome (RM), Italy.
Antonio SantoroHuman Neurosciences Department Neurosurgery Division, "La Sapienza" University, Policlinico Umberto 6 I, viale del Policlinico 155, Rome (RM), 00161, Italy.
Carlo SerraDepartment of Neurosurgery, Clinical Neuroscience Center, University Hospital Zurich, University of Zurch, Frauenklinikstrasse 10, CH-8091, Zurich, Switzerland.
Alessandro FratiIRCCS "Neuromed", via Atinense 18, 86077, Pozzilli, IS, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe goal of glioma surgery is maximal tumor resection associated with minimal post-operative morbidity. Diffusion tensor imaging-tractography/fiber tracking (DTI-FT) is a valuable white-matter (WM) visualization tool for diagnosis and surgical planning. Still, it assumes a descriptive role since the main DTI metrics and parameters showed several limitations in clinical use. New applications and quantitative measurements were recently applied to describe WM architecture that surround the tumor area. The brain adjacent tumor area (BAT) is defined as the region adjacent to the gross tumor volume, which contains signal abnormalities on T2-weighted or FLAIR sequences. The DTI-FT analysis of the BAT can be adopted as predictive values and a guide for safe tumor resection.

methodsThis is an observational prospective study on an extensive series of glioma patients who performed magnetic resonance imaging (MRI) with pre-operative DTI-FT analyzed on the BAT by two different software. We examined DTI parameters of Fractional anisotropy (FA mean, min-max), Mean diffusivity (MD), and the shape-metric "tract irregularity" (TI) grade, comparing it with the surgical series' clinical, radiological, and outcome data.

resultsThe population consisted of 118 patients, with a mean age of 60.6 years. 82 patients suffering from high-grade gliomas (69.5%), and 36 from low-grade gliomas (30.5%). A significant inverse relationship exists between the FA mean value and grading (p = 0.001). The relationship appears directly proportional regarding MD values (p = 0.003) and TI values (p = 0.005). FA mean and MD values are susceptible to significant variations with tumor and edema volume (p = 0.05). TI showed an independent relationship with grading regardless of tumor radiological features and dimensions, with a direct relationship with grading, ki67% (p = 0,05), PFS (p < 0.001), and EOR (p < 0.01).

conclusionFA, MD, and TI are useful predictive measures of the clinical behavior of glioma, and TI could be helpful for tumor grading identification and surgical planning.

Indexed as

Brain NeoplasmsDiffusion Tensor ImagingGliomaAdultAgedAnisotropyFemaleHumansMaleMiddle AgedProspective StudiesTreatment OutcomeWhite MatterYoung AdultDTIGliomaNeurosurgeryTractography

Identifiers

PMID39404938
PMCPMC11685273

What OpenQuestion holds

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Registered trials

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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.