Abstract
Purpose: To develop a fast and automated volume-of-interest (VOI) prescription pipeline (AutoVOI) for single-voxel MRS that removes the need for manual VOI placement, allows flexible VOI planning in any brain region, and enables high inter- and intra-subject consistency of VOI prescription. Methods: AutoVOI was designed to transfer pre-defined VOIs from an atlas to the 3D anatomical data of the subject during the scan. The AutoVOI pipeline was optimized for consistency in VOI placement (precision), enhanced coverage of the targeted tissue (accuracy), and fast computation speed. The tool was evaluated against manual VOI placement using existing T 1 -weighted data sets and corresponding VOI prescriptions. Finally, it was implemented on 2 scanner platforms to acquire MRS data from clinically relevant VOIs that span the cerebrum, cerebellum, and the brainstem. Results: The AutoVOI pipeline includes skull stripping, non-linear registration of the atlas to the subject's brain, and computation of the VOI coordinates and angulations using a minimum oriented bounding box algorithm. When compared against manual prescription, AutoVOI showed higher intra- and inter-subject spatial consistency, as quantified by generalized Dice coefficients (GDC), lower intra- and inter-subject variability in tissue composition (gray matter, white matter, and cerebrospinal fluid) and higher or equal accuracy, as quantified by GDC of prescribed VOI with targeted tissues. High quality spectra were obtained on Siemens and Philips 3T systems from 6 automatically prescribed VOIs by the tool. Conclusion: Robust automatic VOI prescription is feasible and can help facilitate clinical adoption of MRS by avoiding operator dependence of manual selection.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1787-1798 |
| Number of pages | 12 |
| Journal | Magnetic resonance in medicine |
| Volume | 80 |
| Issue number | 5 |
| DOIs | |
| State | Published - Nov 1 2018 |
Fingerprint
Keywords
- MRS
- automation
- generalized dice coefficient
- prescription
- registration
PubMed: MeSH publication types
- Journal Article
- Research Support, N.I.H., Extramural
- Research Support, Non-U.S. Gov't
Cite this
AutoVOI : real-time automatic prescription of volume-of-interest for single voxel spectroscopy. / Park, Young Woo; Deelchand, Dinesh K.; Joers, James M.; Hanna, Brian; Berrington, Adam; Gillen, Joseph S.; Kantarci, Kejal; Soher, Brian J.; Barker, Peter B.; Park, Hyunwook; Öz, Gülin; Lenglet, Christophe.
In: Magnetic resonance in medicine, Vol. 80, No. 5, 01.11.2018, p. 1787-1798.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - AutoVOI
T2 - real-time automatic prescription of volume-of-interest for single voxel spectroscopy
AU - Park, Young Woo
AU - Deelchand, Dinesh K.
AU - Joers, James M.
AU - Hanna, Brian
AU - Berrington, Adam
AU - Gillen, Joseph S.
AU - Kantarci, Kejal
AU - Soher, Brian J.
AU - Barker, Peter B.
AU - Park, Hyunwook
AU - Öz, Gülin
AU - Lenglet, Christophe
PY - 2018/11/1
Y1 - 2018/11/1
N2 - Purpose: To develop a fast and automated volume-of-interest (VOI) prescription pipeline (AutoVOI) for single-voxel MRS that removes the need for manual VOI placement, allows flexible VOI planning in any brain region, and enables high inter- and intra-subject consistency of VOI prescription. Methods: AutoVOI was designed to transfer pre-defined VOIs from an atlas to the 3D anatomical data of the subject during the scan. The AutoVOI pipeline was optimized for consistency in VOI placement (precision), enhanced coverage of the targeted tissue (accuracy), and fast computation speed. The tool was evaluated against manual VOI placement using existing T 1 -weighted data sets and corresponding VOI prescriptions. Finally, it was implemented on 2 scanner platforms to acquire MRS data from clinically relevant VOIs that span the cerebrum, cerebellum, and the brainstem. Results: The AutoVOI pipeline includes skull stripping, non-linear registration of the atlas to the subject's brain, and computation of the VOI coordinates and angulations using a minimum oriented bounding box algorithm. When compared against manual prescription, AutoVOI showed higher intra- and inter-subject spatial consistency, as quantified by generalized Dice coefficients (GDC), lower intra- and inter-subject variability in tissue composition (gray matter, white matter, and cerebrospinal fluid) and higher or equal accuracy, as quantified by GDC of prescribed VOI with targeted tissues. High quality spectra were obtained on Siemens and Philips 3T systems from 6 automatically prescribed VOIs by the tool. Conclusion: Robust automatic VOI prescription is feasible and can help facilitate clinical adoption of MRS by avoiding operator dependence of manual selection.
AB - Purpose: To develop a fast and automated volume-of-interest (VOI) prescription pipeline (AutoVOI) for single-voxel MRS that removes the need for manual VOI placement, allows flexible VOI planning in any brain region, and enables high inter- and intra-subject consistency of VOI prescription. Methods: AutoVOI was designed to transfer pre-defined VOIs from an atlas to the 3D anatomical data of the subject during the scan. The AutoVOI pipeline was optimized for consistency in VOI placement (precision), enhanced coverage of the targeted tissue (accuracy), and fast computation speed. The tool was evaluated against manual VOI placement using existing T 1 -weighted data sets and corresponding VOI prescriptions. Finally, it was implemented on 2 scanner platforms to acquire MRS data from clinically relevant VOIs that span the cerebrum, cerebellum, and the brainstem. Results: The AutoVOI pipeline includes skull stripping, non-linear registration of the atlas to the subject's brain, and computation of the VOI coordinates and angulations using a minimum oriented bounding box algorithm. When compared against manual prescription, AutoVOI showed higher intra- and inter-subject spatial consistency, as quantified by generalized Dice coefficients (GDC), lower intra- and inter-subject variability in tissue composition (gray matter, white matter, and cerebrospinal fluid) and higher or equal accuracy, as quantified by GDC of prescribed VOI with targeted tissues. High quality spectra were obtained on Siemens and Philips 3T systems from 6 automatically prescribed VOIs by the tool. Conclusion: Robust automatic VOI prescription is feasible and can help facilitate clinical adoption of MRS by avoiding operator dependence of manual selection.
KW - MRS
KW - automation
KW - generalized dice coefficient
KW - prescription
KW - registration
UR - http://www.scopus.com/inward/record.url?scp=85044949373&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85044949373&partnerID=8YFLogxK
U2 - 10.1002/mrm.27203
DO - 10.1002/mrm.27203
M3 - Article
VL - 80
SP - 1787
EP - 1798
JO - Magnetic Resonance in Medicine
JF - Magnetic Resonance in Medicine
SN - 0740-3194
IS - 5
ER -