Analysis of MRS voxel placements in brain tumors performed by MRS experts
Motivation: There is no standardized way of prescribing MRS voxels in the lesion. This depends entirely on the MR operator’s expertise and opinion. Goal(s): Our goal was to analyze MRS voxel placements in brain tumors for quantitatively reliable and reproducible voxel placement. Approach: MRS experts placed voxels and visually scored their placements. Placements and scores were compared to tumor characteristics. Results: All experts showed a tendency to place the voxels to fill approximately 30% of voxels with tumor core for different participants. The fraction of tumor core in voxels showed a correlation of 0.76 to the fraction of tumor core in the whole tumor. Impact: Quantitative analysis of MRS voxel placement shows that MRS experts deemed a voxel properly placed when tumor core was adequately included, suggesting widely applicable and objective method of voxel placement and assessment for non-experts in clinical settings.
Authors
- Alexander Lin (ORCID: https://orcid.org/0000-0001-8236-880X)
- Clark C. Chen (ORCID: https://orcid.org/0000-0001-9544-2570)
- Małgorzata Marjańska (ORCID: https://orcid.org/0000-0002-4727-2447)
- Roberto Liserre (ORCID: https://orcid.org/0000-0003-1536-0183)
- Ovidiu C. Andronesi (ORCID: https://orcid.org/0000-0002-7412-0641)
- Thanh Nguyen (ORCID: https://orcid.org/0000-0001-8458-3351)
- Francesca Branzoli (ORCID: https://orcid.org/0000-0001-9792-0492)
- Patrick J. Bolan (ORCID: https://orcid.org/0000-0002-4194-3975)
- Gerd Melkus (ORCID: https://orcid.org/0000-0001-5387-8958)
- Sangyoon Lee (ORCID: https://orcid.org/0009-0005-8825-5175)
Publication Details
- Journal
- Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
- Published
- 2024-11-26
- DOI
- https://doi.org/10.58530/2024/1854
- Citations
- 1
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.40