Evidence map›Paper›PMID 34970486›Full record

ArticleFrontiers in oncology2021

Tracking the Corticospinal Tract in Patients With High-Grade Glioma: Clinical Evaluation of Multi-Level Fiber Tracking and Comparison to Conventional Deterministic Approaches.

Andrey Zhylka, Nico Sollmann, Florian Kofler, Ahmed Radwan, Alberto De Luca, Jens Gempt, Benedikt Wiestler, Bjoern Menze, Sandro M Krieg, Claus Zimmer and 4 more

Abstract read
In one paragraph

Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Review
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  4. Article
  5. Color Maps: Facilitating the Clinical Impact of Quantitative MRI.Journal of magnetic resonance imaging : JMRI · 2025
    Review
  6. Article
  7. Article
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  11. 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

14 authors.

Andrey ZhylkaBiomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands.
Nico SollmannDepartment of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany.
Florian KoflerDepartment of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
Ahmed RadwanDepartment of Imaging and Pathology, Translational MRI, Katholieke Universiteit (KU) Leuven, Leuven, Belgium.
Alberto De LucaImage Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands.
Jens GemptDepartment of Neurosurgery, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
Benedikt WiestlerDepartment of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
Bjoern MenzeImage-Based Biomedical Modeling, Department of Informatics, Technical University of Munich, Munich, Germany.
Sandro M KriegTUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
Claus ZimmerDepartment of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
Jan S KirschkeDepartment of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
Stefan SunaertDepartment of Imaging and Pathology, Translational MRI, Katholieke Universiteit (KU) Leuven, Leuven, Belgium.
Alexander LeemansImage Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands.
Josien P W PluimBiomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

While the diagnosis of high-grade glioma (HGG) is still associated with a considerably poor prognosis, neurosurgical tumor resection provides an opportunity for prolonged survival and improved quality of life for affected patients. However, successful tumor resection is dependent on a proper surgical planning to avoid surgery-induced functional deficits whilst achieving a maximum extent of resection (EOR). With diffusion magnetic resonance imaging (MRI) providing insight into individual white matter neuroanatomy, the challenge remains to disentangle that information as correctly and as completely as possible. In particular, due to the lack of sensitivity and accuracy, the clinical value of widely used diffusion tensor imaging (DTI)-based tractography is increasingly questioned. We evaluated whether the recently developed multi-level fiber tracking (MLFT) technique can improve tractography of the corticospinal tract (CST) in patients with motor-eloquent HGGs. Forty patients with therapy-naïve HGGs (mean age: 62.6 ± 13.4 years, 57.5% males) and preoperative diffusion MRI [repetition time (TR)/echo time (TE): 5000/78 ms, voxel size: 2x2x2 mm

Indexed as

brain tumorcorticospinal tract (CST)diffusion MRIfiber tractographyneurosurgery planning

Identifiers

PMID34970486
PMCPMC8712728

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.