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Simegn GL, Gagoski B, Song Y, Dean DC, Hupfeld KE, Murali-Manohar S, Davies-Jenkins CW, Simičić D, Wisnowski J, Yedavalli V, Gudmundson AT, Zöllner HJ, Oeltzschner G, Edden RAE. Comparison of test-retest reproducibility of DESPOT and 3D-QALAS for water T 1 and T 2 mapping. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.15.608081. [PMID: 39229114 PMCID: PMC11370424 DOI: 10.1101/2024.08.15.608081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 09/05/2024]
Abstract
Purpose Relaxometry, specifically T 1 and T 2 mapping, has become an essential technique for assessing the properties of biological tissues related to various physiological and pathological conditions. Many techniques are being used to estimate T 1 and T 2 relaxation times, ranging from the traditional inversion or saturation recovery and spin-echo sequences to more advanced methods. Choosing the appropriate method for a specific application is critical since the precision and accuracy of T 1 and T 2 measurements are influenced by a variety of factors including the pulse sequence and its parameters, the inherent properties of the tissue being examined, the MRI hardware, and the image reconstruction. The aim of this study is to evaluate and compare the test-retest reproducibility of two advanced MRI relaxometry techniques (Driven Equilibrium Single Pulse Observation of T 1 and T 2, DESPOT, and 3D Quantification using an interleaved Look-Locker acquisition Sequence with a T 2 preparation pulse, QALAS), for T 1 and T 2 mapping in a healthy volunteer cohort. Methods 10 healthy volunteers underwent brain MRI at 1.3 mm3 isotropic resolution, acquiring DESPOT and QALAS data (~11.8 and ~5 minutes duration, including field maps, respectively), test-retest with subject repositioning, on a 3.0 Tesla Philips Ingenia Elition scanner. To reconstruct the T 1 and T 2 maps, we used an equation-based algorithm for DESPOT and a dictionary-based algorithm that incorporates inversion efficiency and B 1 -field inhomogeneity for QALAS. The test-retest reproducibility was assessed using the coefficient of variation (CoV), intraclass correlation coefficient (ICC) and Bland-Altman plots. Results Our results indicate that both the DESPOT and QALAS techniques demonstrate good levels of test-retest reproducibility for T 1 and T 2 mapping across the brain. Higher whole-brain voxel-to-voxel ICCs are observed in QALAS for T 1 (0.84 ± 0.039) and in DESPOT for T 2 (0.897 ± 0.029). The Bland-Altman plots show smaller bias and variability of T 1 estimates for QALAS (mean of -0.02 s, and upper and lower limits of -0.14 and 0.11 s, 95% CI) than for DESPOT (mean of -0.02 s, and limits of -0.31 and 0.27 s). QALAS also showed less variability (mean 1.08 ms, limits -1.88 to 4.04 ms) for T 2 compared to DESPOT (mean of 2.56 ms, and limits -17.29 to 22.41 ms). The within-subject CoVs for QALAS range from 0.6% (T 2 in CSF) to 5.8% (T 2 in GM), while for DESPOT they range from 2.1% (T 2 in CSF) to 6.7% (T 2 in GM). The between-subject CoVs for QALAS range from 2.5% (T 2 in GM) to 12% (T 2 in CSF), and for DESPOT they range from 3.7% (T 2 in WM) to 9.3% (T 2 in CSF). Conclusion Overall, QALAS demonstrated better reproducibility for T 1 and T 2 measurements than DESPOT, in addition to reduced acquisition time.
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Affiliation(s)
- Gizeaddis Lamesgin Simegn
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Borjan Gagoski
- Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Yulu Song
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Douglas C Dean
- Department of Pediatrics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - Kathleen E Hupfeld
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Saipavitra Murali-Manohar
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Christopher W Davies-Jenkins
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Dunja Simičić
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Jessica Wisnowski
- Department of Pediatrics, Division of Neurology, Children's Hospital Los Angeles and the University of Southern California
| | - Vivek Yedavalli
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Aaron T Gudmundson
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
- The Malone Center for Engineering in Healthcare, Johns Hopkins University, Baltimore, MD, USA
| | - Helge J Zöllner
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Georg Oeltzschner
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Richard A E Edden
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
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Uher D, Drenthen GS, Schijns OEMG, Colon AJ, Hofman PAM, van Lanen RHGJ, Hoeberigs CM, Jansen JFA, Backes WH. Advances in Image Processing for Epileptogenic Zone Detection with MRI. Radiology 2023; 307:e220927. [PMID: 37129491 DOI: 10.1148/radiol.220927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Focal epilepsy is a common and severe neurologic disorder. Neuroimaging aims to identify the epileptogenic zone (EZ), preferably as a macroscopic structural lesion. For approximately a third of patients with chronic drug-resistant focal epilepsy, the EZ cannot be precisely identified using standard 3.0-T MRI. This may be due to either the EZ being undetectable at imaging or the seizure activity being caused by a physiologic abnormality rather than a structural lesion. Computational image processing has recently been shown to aid radiologic assessments and increase the success rate of uncovering suspicious regions by enhancing their visual conspicuity. While structural image analysis is at the forefront of EZ detection, physiologic image analysis has also been shown to provide valuable information about EZ location. This narrative review summarizes and explains the current state-of-the-art computational approaches for image analysis and presents their potential for EZ detection. Current limitations of the methods and possible future directions to augment EZ detection are discussed.
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Affiliation(s)
- Daniel Uher
- From the Department of Radiology and Nuclear Medicine (D.U., G.S.D., P.A.M.H., C.M.H., J.F.A.J., W.H.B.) and Department of Neurosurgery (O.E.M.G.S., R.H.G.J.v.L.), Maastricht University Medical Centre, P. Debyelaan 25, NL-6229 HX Maastricht, the Netherlands; School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, the Netherlands (D.U., G.S.D., O.E.M.G.S., R.H.G.J.v.L., J.F.A.J., W.H.B.); Academic Center for Epileptology, Kempenhaeghe and Maastricht University Medical Centre, Heeze/Maastricht, the Netherlands (O.E.M.G.S., A.J.C., P.A.M.H., C.M.H., J.F.A.J.); and Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands (J.F.A.J.)
| | - Gerhard S Drenthen
- From the Department of Radiology and Nuclear Medicine (D.U., G.S.D., P.A.M.H., C.M.H., J.F.A.J., W.H.B.) and Department of Neurosurgery (O.E.M.G.S., R.H.G.J.v.L.), Maastricht University Medical Centre, P. Debyelaan 25, NL-6229 HX Maastricht, the Netherlands; School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, the Netherlands (D.U., G.S.D., O.E.M.G.S., R.H.G.J.v.L., J.F.A.J., W.H.B.); Academic Center for Epileptology, Kempenhaeghe and Maastricht University Medical Centre, Heeze/Maastricht, the Netherlands (O.E.M.G.S., A.J.C., P.A.M.H., C.M.H., J.F.A.J.); and Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands (J.F.A.J.)
| | - Olaf E M G Schijns
- From the Department of Radiology and Nuclear Medicine (D.U., G.S.D., P.A.M.H., C.M.H., J.F.A.J., W.H.B.) and Department of Neurosurgery (O.E.M.G.S., R.H.G.J.v.L.), Maastricht University Medical Centre, P. Debyelaan 25, NL-6229 HX Maastricht, the Netherlands; School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, the Netherlands (D.U., G.S.D., O.E.M.G.S., R.H.G.J.v.L., J.F.A.J., W.H.B.); Academic Center for Epileptology, Kempenhaeghe and Maastricht University Medical Centre, Heeze/Maastricht, the Netherlands (O.E.M.G.S., A.J.C., P.A.M.H., C.M.H., J.F.A.J.); and Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands (J.F.A.J.)
| | - Albert J Colon
- From the Department of Radiology and Nuclear Medicine (D.U., G.S.D., P.A.M.H., C.M.H., J.F.A.J., W.H.B.) and Department of Neurosurgery (O.E.M.G.S., R.H.G.J.v.L.), Maastricht University Medical Centre, P. Debyelaan 25, NL-6229 HX Maastricht, the Netherlands; School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, the Netherlands (D.U., G.S.D., O.E.M.G.S., R.H.G.J.v.L., J.F.A.J., W.H.B.); Academic Center for Epileptology, Kempenhaeghe and Maastricht University Medical Centre, Heeze/Maastricht, the Netherlands (O.E.M.G.S., A.J.C., P.A.M.H., C.M.H., J.F.A.J.); and Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands (J.F.A.J.)
| | - Paul A M Hofman
- From the Department of Radiology and Nuclear Medicine (D.U., G.S.D., P.A.M.H., C.M.H., J.F.A.J., W.H.B.) and Department of Neurosurgery (O.E.M.G.S., R.H.G.J.v.L.), Maastricht University Medical Centre, P. Debyelaan 25, NL-6229 HX Maastricht, the Netherlands; School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, the Netherlands (D.U., G.S.D., O.E.M.G.S., R.H.G.J.v.L., J.F.A.J., W.H.B.); Academic Center for Epileptology, Kempenhaeghe and Maastricht University Medical Centre, Heeze/Maastricht, the Netherlands (O.E.M.G.S., A.J.C., P.A.M.H., C.M.H., J.F.A.J.); and Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands (J.F.A.J.)
| | - Rick H G J van Lanen
- From the Department of Radiology and Nuclear Medicine (D.U., G.S.D., P.A.M.H., C.M.H., J.F.A.J., W.H.B.) and Department of Neurosurgery (O.E.M.G.S., R.H.G.J.v.L.), Maastricht University Medical Centre, P. Debyelaan 25, NL-6229 HX Maastricht, the Netherlands; School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, the Netherlands (D.U., G.S.D., O.E.M.G.S., R.H.G.J.v.L., J.F.A.J., W.H.B.); Academic Center for Epileptology, Kempenhaeghe and Maastricht University Medical Centre, Heeze/Maastricht, the Netherlands (O.E.M.G.S., A.J.C., P.A.M.H., C.M.H., J.F.A.J.); and Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands (J.F.A.J.)
| | - Christianne M Hoeberigs
- From the Department of Radiology and Nuclear Medicine (D.U., G.S.D., P.A.M.H., C.M.H., J.F.A.J., W.H.B.) and Department of Neurosurgery (O.E.M.G.S., R.H.G.J.v.L.), Maastricht University Medical Centre, P. Debyelaan 25, NL-6229 HX Maastricht, the Netherlands; School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, the Netherlands (D.U., G.S.D., O.E.M.G.S., R.H.G.J.v.L., J.F.A.J., W.H.B.); Academic Center for Epileptology, Kempenhaeghe and Maastricht University Medical Centre, Heeze/Maastricht, the Netherlands (O.E.M.G.S., A.J.C., P.A.M.H., C.M.H., J.F.A.J.); and Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands (J.F.A.J.)
| | - Jacobus F A Jansen
- From the Department of Radiology and Nuclear Medicine (D.U., G.S.D., P.A.M.H., C.M.H., J.F.A.J., W.H.B.) and Department of Neurosurgery (O.E.M.G.S., R.H.G.J.v.L.), Maastricht University Medical Centre, P. Debyelaan 25, NL-6229 HX Maastricht, the Netherlands; School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, the Netherlands (D.U., G.S.D., O.E.M.G.S., R.H.G.J.v.L., J.F.A.J., W.H.B.); Academic Center for Epileptology, Kempenhaeghe and Maastricht University Medical Centre, Heeze/Maastricht, the Netherlands (O.E.M.G.S., A.J.C., P.A.M.H., C.M.H., J.F.A.J.); and Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands (J.F.A.J.)
| | - Walter H Backes
- From the Department of Radiology and Nuclear Medicine (D.U., G.S.D., P.A.M.H., C.M.H., J.F.A.J., W.H.B.) and Department of Neurosurgery (O.E.M.G.S., R.H.G.J.v.L.), Maastricht University Medical Centre, P. Debyelaan 25, NL-6229 HX Maastricht, the Netherlands; School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, the Netherlands (D.U., G.S.D., O.E.M.G.S., R.H.G.J.v.L., J.F.A.J., W.H.B.); Academic Center for Epileptology, Kempenhaeghe and Maastricht University Medical Centre, Heeze/Maastricht, the Netherlands (O.E.M.G.S., A.J.C., P.A.M.H., C.M.H., J.F.A.J.); and Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands (J.F.A.J.)
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Del Signore F, Vignoli M, Della Salda L, Tamburro R, Paolini A, Cerasoli I, Chincarini M, Rossi E, Ferri N, Romanucci M, Falerno I, de Pasquale F. A Magnetic Resonance-Relaxometry-Based Technique to Identify Blood Products in Brain Parenchyma: An Experimental Study on a Rabbit Model. Front Vet Sci 2022; 9:802272. [PMID: 35711807 PMCID: PMC9195168 DOI: 10.3389/fvets.2022.802272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Accepted: 04/11/2022] [Indexed: 11/13/2022] Open
Abstract
Magnetic resonance relaxometry is a quantitative technique that estimates T1/T2 tissue relaxation times. This has been proven to increase MRI diagnostic accuracy of brain disorders in human medicine. However, literature in the veterinary field is scarce. In this work, a T1 and T2-based relaxometry approach has been developed. The aim is to investigate its performance in characterizing subtle brain lesions obtained with autologous blood injections in rabbits. This study was performed with a low-field scanner, typically present in veterinary clinics. The approach consisted of a semi-automatic hierarchical classification of different regions, selected from a T2 map. The classification was driven according to the relaxometry properties extracted from a set of regions selected by the radiologist to compare the suspected lesion with the healthy parenchyma. Histopathological analyses were performed to estimate the performance of the proposed classifier through receiver operating characteristic curve analyses. The classifier resulted in moderate accuracy in terms of lesion characterization.
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Affiliation(s)
- Francesca Del Signore
- Veterinary Faculty, University of Teramo, Teramo, Italy
- *Correspondence: Francesca Del Signore
| | | | | | | | | | | | | | - Emanuela Rossi
- Istituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise Giuseppe Caporale, Teramo, Italy
| | - Nicola Ferri
- Istituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise Giuseppe Caporale, Teramo, Italy
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Zhao L, Zhang X, Luo Y, Hu J, Liang C, Wang L, Gao J, Qi X, Zhai F, Shi L, Zhu M. Automated detection of hippocampal sclerosis: Comparison of a composite MRI-based index with conventional MRI measures. Epilepsy Res 2021; 174:106638. [PMID: 33964793 DOI: 10.1016/j.eplepsyres.2021.106638] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Revised: 04/01/2021] [Accepted: 04/06/2021] [Indexed: 11/27/2022]
Abstract
PURPOSE This study aims to compare the performance of an MRI-based composite index (HSI) with conventional MRI-based measures in hippocampal sclerosis (HS) detection and postoperative outcome estimation. METHODS Seventy-two temporal lobe epilepsy (TLE) patients with pathologically confirmed HS and fifteen TLE patients without HS were included retrospectively. The T1-weighted and FLAIR images of these patients were processed with AccuBrain to quantify the hippocampal volume (HV) and the hippocampal FLAIR signal. The HSI index that considered both HV and hippocampal FLAIR signal was also calculated. Two experienced neuropathologists rated the HS severity with the resected tissue and reached an agreement for all cases. The asymmetry indices of the MRI measures were used to lateralize the sclerotic side, and the original MRI measures were applied to detect HS vs. normal hippocampi. Operating characteristic curve (ROC) analyses were performed for these predictions. We also investigated the sensitivity of the ipsilateral MRI measures in characterizing the pathological severity of HS and the associations of the MRI measures with postoperative outcomes (Engel class categories). RESULTS With the optimal cutoffs, the asymmetry indices of HSI and HV both achieved excellent performance in differentiating left vs. right HS (accuracy = 100 %), and the absolute value of the asymmetry index of HSI performed best in differentiating unilateral vs. bilateral HS (accuracy = 91.7 %). Regarding the detection of HS, HSI performed better in sensitivity (94.4 % vs. 87.5 %) while HV performed better in specificity (93.6 % vs. 89.4 %) when the contralateral site of unilateral HS and both sides of non-HS patients were considered as the normal reference, and HSI performed even better than HV when only both sides of non-HS patients were considered as the normal reference (AUC: 0.956 vs. 0.934, p = 0.038). The ipsilateral HSI presented the strongest association with the pathological rating of HS severity (r = 0.405, p < 0.001). None of the ipsilateral or contralateral MRI measures was associated with the postoperative outcomes. Among the asymmetry indices, only the absolute value of the asymmetry index of HV presented a significant association with the Engel classifications for the Year 2∼3 visit (r = -0.466, p = 0.004) or the latest visit with >1 year follow-up (r = -0.374, p = 0.003) while controlling for disease duration and follow-up duration. CONCLUSION The HSI index and HV presented comparable good performance in HS detection, and HSI may have better sensitivity than HV in differentiating pathological HS severity. Higher magnitude of HV dissymmetry may indicate better post-surgical outcomes for HS patients.
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Affiliation(s)
- Lei Zhao
- BrainNow Research Institute, Shenzhen, China
| | - Xufei Zhang
- Department of Radiology, Sanbo Brain Hospital, Capital Medical University, China
| | - Yishan Luo
- BrainNow Research Institute, Shenzhen, China
| | - Jianxin Hu
- Department of Radiology, Sanbo Brain Hospital, Capital Medical University, China
| | - Chenyang Liang
- Department of Radiology, Sanbo Brain Hospital, Capital Medical University, China
| | - Lining Wang
- Department of Radiology, Sanbo Brain Hospital, Capital Medical University, China
| | - Jie Gao
- Department of Radiology, Sanbo Brain Hospital, Capital Medical University, China
| | - Xueling Qi
- Department of Pathology, Sanbo Brain Hospital, Capital Medical University, China
| | - Feng Zhai
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, China
| | - Lin Shi
- BrainNow Research Institute, Shenzhen, China; Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China.
| | - Mingwang Zhu
- Department of Radiology, Sanbo Brain Hospital, Capital Medical University, China.
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