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Sankaralayam DS, Ramaniharan AK, Gupta RK, Patir R, Ahlawat S, Vaishya S, Singh A. Evaluating the Role of Leakage Correction of Hemodynamic Parameters derived from Dynamic Contrast Enhanced MRI for Glioma Grading. J Magn Reson Imaging 2024. [PMID: 38461487 DOI: 10.1002/jmri.29338] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 02/22/2024] [Accepted: 02/22/2024] [Indexed: 03/12/2024] Open
Affiliation(s)
- Dinil Sasi Sankaralayam
- Centre for Biomedical Engineering, Indian Institute of Technology Delhi, New Delhi, India
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Anandh K Ramaniharan
- Philips Innovation Campus, Philips Healthcare India Private Limited, Bangalore, Karnataka, India
| | - Rakesh Kumar Gupta
- Department of Radiology and Imaging, Fortis Memorial Research Institute, Gurugram, Haryana, India
| | - Rana Patir
- Department of Neurosurgery, Fortis Memorial Research Institute, Gurugram, Haryana, India
| | - Sunita Ahlawat
- SRL Diagnostics, Fortis Memorial Research Institute, Gurugram, Haryana, India
| | - Sandeep Vaishya
- Department of Radiology and Imaging, Fortis Memorial Research Institute, Gurugram, Haryana, India
| | - Anup Singh
- Centre for Biomedical Engineering, Indian Institute of Technology Delhi, New Delhi, India
- Department of Biomedical Engineering, All India Institute of Medical Sciences, New Delhi, India
- Yardi School of Artificial Intelligence, Indian Institute of Technology Delhi, New Delhi, India
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Minosse S, Picchi E, Ferrazzoli V, Pucci N, Da Ros V, Giocondo R, Floris R, Garaci F, Di Giuliano F. Influence of scan duration on dynamic contrast -enhanced magnetic resonance imaging pharmacokinetic parameters for brain lesions. Magn Reson Imaging 2024; 105:46-56. [PMID: 37939968 DOI: 10.1016/j.mri.2023.11.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 11/01/2023] [Accepted: 11/04/2023] [Indexed: 11/10/2023]
Abstract
OBJECTIVE Gadolinium-based contrast agent needs time to leak into the extravascular-extracellular space, leak back into the vascular space, and reach an equilibrium state. For this reason, acquisition times of <10 min may cause inaccurate estimation of pharmacokinetic parameters. Since no studies have been conducted on the influence of long scan times on DCE-MRI parameters in brain tumors, the aim of this study is to investigate the variation of DCE-MRI-derived kinetic parameters as a function of acquisition time, from 5 to 10 min in brain tumors. MATERIALS AND METHODS Fifty-two patients with histologically confirmed brain tumors were enrolled in this retrospective study, and examination at 3 T, DCE-MRI, with scan duration of 10 min, was used for retrospective generation of 6 sets of quantitative DCE-MRI maps (Ktrans, Ve and Kep) from 5 to 10 min. Features were extracted from the DCE-MRI maps in contrast enhancement (CE) volumes. Kruskal-Wallis with post-hoc correction and coefficient of variation (CoV) were used as statistical test to compare DCE-MRI maps obtained from 6 data sets. SIGNIFICANCE p < 0.05. RESULTS No differences in Ktrans features in CE volumes between different scan durations. Ve, Kep features in CE volumes were influenced by different data length. The highest number of significantly different Ve and Kep features in CE volumes were between 5 min and 10 min (p < 0.013), 5 min and 9 min (p < 0.044), 6 min and 10 min (p < 0.040). CoV of Kep was reduced from 5 min to 10 min, going from highly variable (CoV = 0.70) to mildly variable (CoV = 0.42). CONCLUSION Kep and Ve were time-dependent in brain tumors, so a longer scan time is needed to obtain reliable parameter values. Ktrans was found to be time-independent, as it remains the same in all 6 acquisition times and is the only reliable parameter with short acquisition times.
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Affiliation(s)
- Silvia Minosse
- Diagnostic Imaging Unit, Department of Biomedicine and Prevention, University of Rome Tor Vergata, Viale Oxford 81, Rome 00133, Italy.
| | - Eliseo Picchi
- Diagnostic Imaging Unit, Department of Biomedicine and Prevention, University of Rome Tor Vergata, Viale Oxford 81, Rome 00133, Italy; Department of Biomedicine and Prevention, University of Rome Tor Vergata, Via Montpellier 1, Rome 00133, Italy
| | - Valentina Ferrazzoli
- Neuroradiology Unit, Department of Biomedicine and Prevention, University of Rome Tor Vergata, Viale Oxford 81, Rome 00133, Italy; Department of Biomedicine and Prevention, University of Rome Tor Vergata, Via Montpellier 1, Rome 00133, Italy
| | - Noemi Pucci
- Diagnostic Imaging Unit, Department of Biomedicine and Prevention, University of Rome Tor Vergata, Viale Oxford 81, Rome 00133, Italy; Department of Biomedicine and Prevention, University of Rome Tor Vergata, Via Montpellier 1, Rome 00133, Italy
| | - Valerio Da Ros
- Diagnostic Imaging Unit, Department of Biomedicine and Prevention, University of Rome Tor Vergata, Viale Oxford 81, Rome 00133, Italy; Department of Biomedicine and Prevention, University of Rome Tor Vergata, Via Montpellier 1, Rome 00133, Italy
| | - Raffaella Giocondo
- Department of Biomedicine and Prevention, University of Rome Tor Vergata, Via Montpellier 1, Rome 00133, Italy
| | - Roberto Floris
- Diagnostic Imaging Unit, Department of Biomedicine and Prevention, University of Rome Tor Vergata, Viale Oxford 81, Rome 00133, Italy; Department of Biomedicine and Prevention, University of Rome Tor Vergata, Via Montpellier 1, Rome 00133, Italy
| | - Francesco Garaci
- Neuroradiology Unit, Department of Biomedicine and Prevention, University of Rome Tor Vergata, Viale Oxford 81, Rome 00133, Italy; Department of Biomedicine and Prevention, University of Rome Tor Vergata, Via Montpellier 1, Rome 00133, Italy; San Raffaele Cassino, Via Gaetano di Biasio 1, Cassino 03043, Italy
| | - Francesca Di Giuliano
- Neuroradiology Unit, Department of Biomedicine and Prevention, University of Rome Tor Vergata, Viale Oxford 81, Rome 00133, Italy; Department of Biomedicine and Prevention, University of Rome Tor Vergata, Via Montpellier 1, Rome 00133, Italy
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Li KL, Lewis D, Zhu X, Coope DJ, Djoukhadar I, King AT, Cootes T, Jackson A. A Novel Multi-Model High Spatial Resolution Method for Analysis of DCE MRI Data: Insights from Vestibular Schwannoma Responses to Antiangiogenic Therapy in Type II Neurofibromatosis. Pharmaceuticals (Basel) 2023; 16:1282. [PMID: 37765090 PMCID: PMC10534691 DOI: 10.3390/ph16091282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 09/01/2023] [Accepted: 09/05/2023] [Indexed: 09/29/2023] Open
Abstract
This study aimed to develop and evaluate a new DCE-MRI processing technique that combines LEGATOS, a dual-temporal resolution DCE-MRI technique, with multi-kinetic models. This technique enables high spatial resolution interrogation of flow and permeability effects, which is currently challenging to achieve. Twelve patients with neurofibromatosis type II-related vestibular schwannoma (20 tumours) undergoing bevacizumab therapy were imaged at 1.5 T both before and at 90 days following treatment. Using the new technique, whole-brain, high spatial resolution images of the contrast transfer coefficient (Ktrans), vascular fraction (vp), extravascular extracellular fraction (ve), capillary plasma flow (Fp), and the capillary permeability-surface area product (PS) could be obtained, and their predictive value was examined. Of the five microvascular parameters derived using the new method, baseline PS exhibited the strongest correlation with the baseline tumour volume (p = 0.03). Baseline ve showed the strongest correlation with the change in tumour volume, particularly the percentage tumour volume change at 90 days after treatment (p < 0.001), and PS demonstrated a larger reduction at 90 days after treatment (p = 0.0001) when compared to Ktrans or Fp alone. Both the capillary permeability-surface area product (PS) and the extravascular extracellular fraction (ve) significantly differentiated the 'responder' and 'non-responder' tumour groups at 90 days (p < 0.05 and p < 0.001, respectively). These results highlight that this novel DCE-MRI analysis approach can be used to evaluate tumour microvascular changes during treatment and the need for future larger clinical studies investigating its role in predicting antiangiogenic therapy response.
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Affiliation(s)
- Ka-Loh Li
- Division of Informatics, Imaging and Data Sciences, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PL, UK; (K.-L.L.); (T.C.); (A.J.)
- Geoffrey Jefferson Brain Research Centre, University of Manchester, Manchester M13 9PL, UK; (D.L.); (D.J.C.); (A.T.K.)
| | - Daniel Lewis
- Geoffrey Jefferson Brain Research Centre, University of Manchester, Manchester M13 9PL, UK; (D.L.); (D.J.C.); (A.T.K.)
- Department of Neurosurgery, Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester M13 9NT, UK
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PL, UK
| | - Xiaoping Zhu
- Division of Informatics, Imaging and Data Sciences, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PL, UK; (K.-L.L.); (T.C.); (A.J.)
- Wolfson Molecular Imaging Centre, University of Manchester, 27 Palatine Road, Manchester M20 3LJ, UK
| | - David J. Coope
- Geoffrey Jefferson Brain Research Centre, University of Manchester, Manchester M13 9PL, UK; (D.L.); (D.J.C.); (A.T.K.)
- Department of Neurosurgery, Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester M13 9NT, UK
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PL, UK
| | - Ibrahim Djoukhadar
- Department of Neuroradiology, Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester M13 9NT, UK;
| | - Andrew T. King
- Geoffrey Jefferson Brain Research Centre, University of Manchester, Manchester M13 9PL, UK; (D.L.); (D.J.C.); (A.T.K.)
- Department of Neurosurgery, Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester M13 9NT, UK
- Division of Cardiovascular Sciences, School of Medical Sciences, Faculty of Biology Medicine and Health, University of Manchester, Manchester M13 9PL, UK
| | - Timothy Cootes
- Division of Informatics, Imaging and Data Sciences, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PL, UK; (K.-L.L.); (T.C.); (A.J.)
| | - Alan Jackson
- Division of Informatics, Imaging and Data Sciences, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PL, UK; (K.-L.L.); (T.C.); (A.J.)
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Wu J, Liang Z, Deng X, Xi Y, Feng X, Yao Z, Shu Z, Xie Q. Glioma grade discrimination with dynamic contrast-enhanced MRI: An accurate analysis based on MRI guided stereotactic biopsy. Magn Reson Imaging 2023; 99:91-97. [PMID: 36803634 DOI: 10.1016/j.mri.2023.02.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2022] [Revised: 02/05/2023] [Accepted: 02/06/2023] [Indexed: 02/17/2023]
Abstract
PURPOSE To evaluate the diagnostic performance of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) metrics for glioma grading on a point-to-point basis. METHODS Forty patients with treatment-naïve glioma underwent DCE-MR examination and stereotactic biopsy. DCE-derived parameters including endothelial transfer constant (Ktrans), volume of extravascular-extracellular space (ve), fractional plasma volume (fpv), and reflux transfer rate (kep) were measured within ROIs on DCE maps accurately matched with biopsies used for histologic grades diagnosis. Differences in parameters between grades were evaluated by Kruskal-Wallis tests. Diagnostic accuracy of each parameter and their combination was assessed using receiver operating characteristic curve. RESULTS Eighty-four independent biopsy samples from 40 patients were analyzed in our study. Significant statistical differences in Ktrans and ve were observed between grades except ve between grade 2 and 3. Ktrans showed good to excellent accuracy in discriminating grade 2 from 3, 3 from 4, and 2 from 4 (area under the curve = 0.802, 0.801 and 0.971, respectively). Ve indicated good accuracy in discriminating grade 3 from 4 and 2 from 4 (AUC = 0.874 and 0.899, respectively). The combined parameter demonstrated fair to excellent accuracy in discriminating grade 2 from 3, 3 from 4, and 2 from 4 (AUC = 0.794, 0.899 and 0.982, respectively). CONCLUSION Our study had identified Ktrans, ve and the combination of parameters to be an accurate predictor for grading glioma.
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Affiliation(s)
- Juan Wu
- Department of Radiology, Shanghai TCM-Integrated Hospital affiliated to Shanghai University of Traditional Chinese Medicine, NO. 230 Dalian Road, Shanghai 200082, PR China
| | - Zonghui Liang
- Department of Radiology, Jing'an District Centre Hospital, Fudan University, NO. 266 Xikang Road, Shanghai 200040, PR China
| | - Xiaofei Deng
- Department of Radiology, Shanghai TCM-Integrated Hospital affiliated to Shanghai University of Traditional Chinese Medicine, NO. 230 Dalian Road, Shanghai 200082, PR China
| | - Yan Xi
- Department of Radiology, Shanghai TCM-Integrated Hospital affiliated to Shanghai University of Traditional Chinese Medicine, NO. 230 Dalian Road, Shanghai 200082, PR China
| | - Xiaoyuan Feng
- Department of Radiology, Huashan Hospital, Fudan University, Mid Wulumuqi Road, Shanghai 200040, PR China
| | - Zhenwei Yao
- Department of Radiology, Huashan Hospital, Fudan University, Mid Wulumuqi Road, Shanghai 200040, PR China.
| | - Zheng Shu
- Department of Radiology, Shanghai TCM-Integrated Hospital affiliated to Shanghai University of Traditional Chinese Medicine, NO. 230 Dalian Road, Shanghai 200082, PR China.
| | - Qian Xie
- Department of Radiology, Jing'an District Centre Hospital, Fudan University, NO. 266 Xikang Road, Shanghai 200040, PR China.
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Exploration of CT Images Based on the BN-U-net-W Network Segmentation Algorithm in Glioma Surgery. CONTRAST MEDIA & MOLECULAR IMAGING 2022; 2022:4476412. [PMID: 35494212 PMCID: PMC9017567 DOI: 10.1155/2022/4476412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Revised: 02/19/2022] [Accepted: 02/21/2022] [Indexed: 11/17/2022]
Abstract
This study aimed to explore the application value of computed tomography (CT) imaging features based on the deep learning batch normalization (batch normalization, BN) U-net-W network image segmentation algorithm in evaluating and diagnosing glioma surgery. 72 patients with glioma who were admitted to hospital were selected as the research subjects. They were divided into a low-grade group (grades I-II, N = 27 cases) and high-grade group (grades III-IV, N = 45 cases) according to postoperative pathological examination results. The CT perfusion imaging (CTPI) images of patients were processed by using the deep learning-based BN-U-net-W network image segmentation algorithm. The application value of the algorithm was comprehensively evaluated by comparing the average Dice coefficient, average recall rate, and average precision of the BN-U-net-W network image segmentation algorithm with the U-net and BN-U-net network algorithms. The results showed that the Dice coefficient, recall, and precision of the BN-U-net-W network were 86.31%, 88.43%, and 87.63% respectively, which were higher than those of the U-net and BN-U-net networks, and the differences were statistically significant (P < 0.05). Cerebral blood flow (CBF), cerebral blood volume (CBV), and capillary permeability (PMB) in the glioma area were 56.85 mL/(min·100 g), 18.03 mL/(min·100 g), and 8.57 mL/100 g, respectively, which were significantly higher than those of normal brain tissue, showing statistically significant differences (P < 0.05). The mean transit time (MTT) difference between the two was not statistically significant (P > 0.05). The receiver operating characteristic (ROC) curves of CBF, CBV, and PMB in CTPI parameters of glioma had area under the curve (AUC) of 0.685, 0.724, and 0.921, respectively. PMB parameters were significantly higher than those of CBF and CVB, and the differences were statistically obvious (P < 0.05). It showed that the BN-U-net-W network model had a better image segmentation effect, and CBF, CBV, and PMB showed better sensitivity in diagnosing glioma tissue and normal brain tissue and high-grade and low-grade gliomas, among which PBM showed the highest predictability.
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Follow-Up of High-Grade Glial Tumor; Differentiation of Posttreatment Enhancement and Tumoral Enhancement by DCE-MR Perfusion. CONTRAST MEDIA & MOLECULAR IMAGING 2022; 2022:6948422. [PMID: 35185410 PMCID: PMC8825574 DOI: 10.1155/2022/6948422] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Revised: 11/21/2021] [Accepted: 01/11/2022] [Indexed: 02/04/2023]
Abstract
Purpose To search for the utility of DCE-MRP to differentiate between posttreatment enhancement (PT) and tumoral enhancement (TM) in high-grade glial tumors. Materials and Methods Thirty-four patients with glioma (11 grade 3; 23 grade 4) were enrolled. Enhancement in the vicinity of the resection cavity demonstrated by DCE-MRP was taken into consideration. Based on the follow-up scans, reoperation or biopsy results, the enhancement type was categorized as PT or TM. Measurements were performed at the enhancing area near the resection cavity (ERC), nearby (NNA) and contralateral nonenhancing areas (CLNA). Perfusion parameters of the ERC were also subtracted from NNA and CLNA. Intragroup comparison (paired sample t-test) and intergroup comparison (Student's t-test) were made. Results There were 7 PTs and 27 TMs. In the PT, the subtracted values of Ve and IAUC from the CLNA and NNA and the subtracted value of Kep from NNA were statistically different. In TM, all metrics were significantly different comparing the CLNA and NNA. Comparing PT with TM, Ktrans, IAUC, Kep, and subtracted values of Ktrans and IAUC from both NNA and CLNA were significantly different. Conclusions In PT, only Ktrans values did not reveal any difference comparing NNA and CLNA. To differentiate PT from TM, Ktrans, Kep, IAUC, and subtracted values of Ktrans and IAUC from NNA and CLNA can be used. These findings are in concordance with literature.
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