Evidence map›Paper›PMID 38173977›Full record

ArticleRadiology research and practice2021

Clinical Application of Magnetic Resonance Spectroscopy in Diagnosis of Intracranial Mass Lesions.

Callen Kwamboka Onyambu, Mufaddal Nuruddin Wajihi, Alfred Otieno Odhiambo

Open access · goldAbstract read
In one paragraph

Article in Radiology research and practice, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.0field-weighted citation impact, top 26% 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

3 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Review
  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

3 authors at 2 institutions in 1 country.

Callen Kwamboka OnyambuDepartment of Diagnostic Imaging and Radiation Medicine, University of Nairobi, Box 19676-00202, Nairobi, Kenya.ORCID https://orcid.org/0000-0003-4378-5832
Mufaddal Nuruddin WajihiNairobi West Hospital, Box 15695-00509, Nairobi, Kenya.
Alfred Otieno OdhiamboDepartment of Diagnostic Imaging and Radiation Medicine, University of Nairobi, Box 19676-00202, Nairobi, Kenya.
University of Nairobi · KENairobi Hospital · KE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Conventional MR imaging provides highly detailed anatomic information with unrivalled soft tissue contrast making it the mainstay in the diagnosis of suspected brain lesions. Despite this, MRI alone at times cannot answer the diagnostic questions in quite a few patients. Proton MR Spectroscopy (H-MRS) provides information on the metabolic composition within an area under interrogation. By comparing the relative concentrations of specific metabolites, the neuroradiologist can deduce critical information regarding neuronal cell density and integrity, cell membrane turnover, metabolic fuel, and possible necrosis in the region of interest. This provides a biochemical picture of the underlying pathology and thus aids in the diagnosis. Methods: This was a cross-sectional comparative study. Results: Of the 63 patients examined by MRI and MRS for intracranial mass lesions, the radiologists were able to offer a single imaging diagnosis based on MRI alone in only 15 patients (23.8%) while when MRI imaging was combined with MR spectroscopy, a single imaging diagnosis was offered in 47 patients (74.6%). This was an overall statistically significant improvement. Conclusion: MRS aided the radiologist in offering a single diagnosis in high versus low-grade gliomas, high-grade gliomas versus tuberculomas, and recurrent tumours versus radiation necrosis.

Identifiers

PMID38173977
PMCPMC10763544
OpenAlexW3132724183

What OpenQuestion holds

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LicenceCC BY
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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.