Evidence map›Paper›PMID 21210073›Full record

ReviewMolecular medicine (Cambridge, Mass.)

Current molecular imaging of spinal tumors in clinical practice.

Nora Sandu, Gabriele Pöpperl, Marie-Elisabeth Toubert, Toma Spiriev, Belachew Arasho, Mikael Orabi, Bernhard Schaller

Open access · goldAbstract readReview
In one paragraph

Review in Molecular medicine (Cambridge, Mass.). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 2 pooled it
5.0field-weighted citation impact, top 5% 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

20 citing papers in PubMed, 2 syntheses or guidelines pooled it, 36 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Article
  5. Review
  6. New anti-cancer explorations based on metal ions.Journal of nanobiotechnology · 2022
    Review
  7. Article
  8. Intramedullary spinal cord metastases and whole bodyQuantitative imaging in medicine and surgery · 2019
    Article
  9. Review
  10. Article
  11. Oncology letters · 2016
    Article
  12. Article
  13. Review
  14. Molecular imaging for stem cell therapy in the brain.Stem cell research & therapy · 2015
    Article
  15. Article
  16. Spinal molecular imaging by (68) Ga-DOTATATE-positron emission tomography.Journal of craniovertebral junction & spine · 2014
    Article
  17. Commentary.Journal of neurosciences in rural practice · 2014
    Article
  18. Article
  19. Article
  20. 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

7 authors at 3 institutions in 4 countries.

Nora SanduDepartment of Neurological Surgery, Lariboisière Hospital, Universities of Paris, France.
Gabriele Pöpperl
Marie-Elisabeth Toubert
Toma Spiriev
Belachew Arasho
Mikael Orabi
Bernhard Schaller
Hôpital Lariboisière · FRUniversité Paris Cité · FRUniversity of Oradea · RO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Energy metabolism measurements in spinal cord tumors, as well as in osseous spinal tumors/metastasis in vivo, are rarely performed only with molecular imaging (MI) by positron emission tomography (PET). This imaging modality developed from a small number of basic clinical science investigations followed by subsequent work that influenced and enhanced the research of others. Apart from precise anatomical localization by coregistration of morphological imaging and quantification, the most intriguing advantage of this imaging is the opportunity to investigate the time course (dynamics) of disease-specific molecular events in the intact organism. Most importantly, MI represents one of the key technologies in translational molecular neuroscience research, helping to develop experimental protocols that may later be applied to human patients. PET may help monitor a patient at the vertebral level after surgery and during adjuvant treatment for recurrent or progressive disease. Common clinical indications for MI of primary or secondary CNS spinal tumors are: (i) tumor diagnosis, (ii) identification of the metabolically active tumor compartments (differentiation of viable tumor tissue from necrosis) and (iii) prediction of treatment response by measurement of tumor perfusion or ischemia. While spinal PET has been used under specific circumstances, a question remains as to whether the magnitude of biochemical alterations observed by MI in CNS tumors in general (specifically spinal tumors) can reveal any prognostic value with respect to survival. MI may be able to better identify early disease and to differentiate benign from malignant lesions than more traditional methods. Moreover, an adequate identification of treatment effectiveness may influence patient management. MI probes could be developed to image the function of targets without disturbing them or as treatment to modify the target's function. MI therefore closes the gap between in vitro and in vivo integrative biology of disease. At the spinal level, MI may help to detect progression or recurrence of metastatic disease after surgical treatment. In cases of nonsurgical treatments such as chemo-, hormone- or radiotherapy, it may better assess biological efficiency than conventional imaging modalities coupled with blood tumor markers. In fact, PET provides a unique possibility to correlate topography and specific metabolic activity, but it requires additional clinical and experimental experience and research to find new indications for primary or secondary spinal tumors.

Indexed as

Disease ProgressionHumansMolecular ImagingNeoplasm MetastasisPositron-Emission TomographyReproducibility of ResultsSensitivity and SpecificitySpinal Cord NeoplasmsSpinal Neoplasms

Identifiers

PMID21210073
PMCPMC3060992
OpenAlexW934463204

What OpenQuestion 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 OpenQuestion graph.