multimodal magnetic resonance imaging increases the overall diagnostic accuracy in brain tumours: correlation with histopathology

multimodal magnetic resonance imaging increases the overall diagnostic accuracy in brain tumours: correlation with histopathology

;Kasim Abul-Kasim;Majda Thurnher;Stefan Puchner;Pia Sundgren
annales pharmaceutiques francaises 2013 Vol. 17 pp. 4-10
164
abul-kasim2013southmultimodal

Abstract

Background: The aim of this retrospective study was to assess the contribution of multimodal MRI techniques, specifically perfusion-weighted imaging (PWI), and/or MR spectroscopy (MRS), in increasing the diagnostic accuracy of MRI in brain tumours. Methods: Forty-four patients with suspected brain tumours (27 (61%) patients male, mean age 58±17 (mean±SD) years) were included in this retrospective analysis. Patients were examined with conventional MR sequences, DWI, and with PWI and/or MRS. The concordance between the diagnoses obtained with multimodal MRI and with the conventional MR sequences, and the final diagnosis obtained by biopsy, was estimated. Fisher’s exact test and/or chi-square test was performed to estimate the added utility of multimodal MRI. Statistical significance was set at p<0.05. Results: With multimodal MRI, the diagnosis in 41 (93%) patients was the same as that obtained by biopsy, compared with 39% (17/44) patients when the readers were allowed to give one diagnostic possibility during the evaluation of the conventional MR sequences alone (p<0.001). The concordance between the diagnoses provided by evaluating the multimodal MRIs and the final diagnoses was almost perfect (κ value 0.92, 95% CI 0.82 - 1). PWI primarily helped to differentiate lymphomas from other solid tumours, whereas MRS helped to differentiate malignant glioma from metastasis. Both PWI and MRS helped in grading astrocytomas. Conclusion: Multimodal MRI increases diagnostic accuracy and should, wherever available, be performed in the work-up of brain tumours, although this entails increased examination cost and time.

Citation

ID: 238385
Ref Key: abul-kasim2013southmultimodal
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
238385
Unique Identifier:
10.4102/sajr.v17i1.202
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet