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Du S, Gong G, Liu R, Meng K, Yin Y. Advances in determining the gross tumor target volume for radiotherapy of brain metastases. Front Oncol 2024; 14:1338225. [PMID: 38779095 PMCID: PMC11109437 DOI: 10.3389/fonc.2024.1338225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Accepted: 04/19/2024] [Indexed: 05/25/2024] Open
Abstract
Brain metastases (BMs) are the most prevalent intracranial malignant tumors in adults and are the leading cause of mortality attributed to malignant brain diseases. Radiotherapy (RT) plays a critical role in the treatment of BMs, with local RT techniques such as stereotactic radiosurgery (SRS)/stereotactic body radiotherapy (SBRT) showing remarkable therapeutic effectiveness. The precise determination of gross tumor target volume (GTV) is crucial for ensuring the effectiveness of SRS/SBRT. Multimodal imaging techniques such as CT, MRI, and PET are extensively used for the diagnosis of BMs and GTV determination. With the development of functional imaging and artificial intelligence (AI) technology, there are more innovative ways to determine GTV for BMs, which significantly improve the accuracy and efficiency of the determination. This article provides an overview of the progress in GTV determination for RT in BMs.
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Affiliation(s)
- Shanshan Du
- Department of Oncology, Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China
- Department of Radiation Oncology Physics and Technology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Guanzhong Gong
- Department of Radiation Oncology Physics and Technology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Rui Liu
- Department of Radiation Oncology Physics and Technology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Kangning Meng
- Department of Radiation Oncology Physics and Technology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Yong Yin
- Department of Oncology, Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China
- Department of Radiation Oncology Physics and Technology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
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Wang M, Ma Y, Li L, Pan X, Wen Y, Qiu Y, Guo D, Zhu Y, Lian J, Tong D. Compressed Sensitivity Encoding Artificial Intelligence Accelerates Brain Metastasis Imaging by Optimizing Image Quality and Reducing Scan Time. AJNR Am J Neuroradiol 2024; 45:444-452. [PMID: 38485196 DOI: 10.3174/ajnr.a8161] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Accepted: 12/25/2023] [Indexed: 04/10/2024]
Abstract
BACKGROUND AND PURPOSE Accelerating the image acquisition speed of MR imaging without compromising the image quality is challenging. This study aimed to evaluate the feasibility of contrast-enhanced (CE) 3D T1WI and CE 3D-FLAIR sequences reconstructed with compressed sensitivity encoding artificial intelligence (CS-AI) for detecting brain metastases (BM) and explore the optimal acceleration factor (AF) for clinical BM imaging. MATERIALS AND METHODS Fifty-one patients with cancer with suspected BM were included. Fifty participants underwent different customized CE 3D-T1WI or CE 3D-FLAIR sequence scans. Compressed SENSE encoding acceleration 6 (CS6), a commercially available standard sequence, was used as the reference standard. Quantitative and qualitative methods were used to evaluate image quality. The SNR and contrast-to-noise ratio (CNR) were calculated, and qualitative evaluations were independently conducted by 2 neuroradiologists. After exploring the optimal AF, sample images were obtained from 1 patient by using both optimized sequences. RESULTS Quantitatively, the CNR of the CS-AI protocol for CE 3D-T1WI and CE 3D-FLAIR sequences was superior to that of the CS protocol under the same AF (P < .05). Compared with reference CS6, the CS-AI groups had higher CNR values (all P < .05), with the CS-AI10 scan having the highest value. The SNR of the CS-AI group was better than that of the reference for both CE 3D-T1WI and CE 3D-FLAIR sequences (all P < .05). Qualitatively, the CS-AI protocol produced higher image quality scores than did the CS protocol with the same AF (all P < .05). In contrast to the reference CS6, the CS-AI group showed good image quality scores until an AF of up to 10 (all P < .05). The CS-AI10 scan provided the optimal images, improving the delineation of normal gray-white matter boundaries and lesion areas (P < .05). Compared with the reference, CS-AI10 showed reductions in scan time of 39.25% and 39.93% for CE 3D-T1WI and CE 3D-FLAIR sequences, respectively. CONCLUSIONS CE 3D-T1WI and CE 3D-FLAIR sequences reconstructed with CS-AI for the detection of BM may provide a more effective alternative reconstruction approach than CS. CS-AI10 is suitable for clinical applications, providing optimal image quality and a shortened scan time.
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Affiliation(s)
- Mengmeng Wang
- From the Department of Radiology (M.W., Y.M., L.L., X.P., Y.W., Y.Q., D.G., D.T.), The First Hospital of Jilin University, Changchun, China
| | - Yue Ma
- From the Department of Radiology (M.W., Y.M., L.L., X.P., Y.W., Y.Q., D.G., D.T.), The First Hospital of Jilin University, Changchun, China
| | - Linna Li
- From the Department of Radiology (M.W., Y.M., L.L., X.P., Y.W., Y.Q., D.G., D.T.), The First Hospital of Jilin University, Changchun, China
| | - Xingchen Pan
- From the Department of Radiology (M.W., Y.M., L.L., X.P., Y.W., Y.Q., D.G., D.T.), The First Hospital of Jilin University, Changchun, China
| | - Yafei Wen
- From the Department of Radiology (M.W., Y.M., L.L., X.P., Y.W., Y.Q., D.G., D.T.), The First Hospital of Jilin University, Changchun, China
| | - Ying Qiu
- From the Department of Radiology (M.W., Y.M., L.L., X.P., Y.W., Y.Q., D.G., D.T.), The First Hospital of Jilin University, Changchun, China
| | - Dandan Guo
- From the Department of Radiology (M.W., Y.M., L.L., X.P., Y.W., Y.Q., D.G., D.T.), The First Hospital of Jilin University, Changchun, China
| | - Yi Zhu
- Philips Healthcare (Y.Z., J.L., D.T.), Beijing, China
| | - Jianxiu Lian
- Philips Healthcare (Y.Z., J.L., D.T.), Beijing, China
| | - Dan Tong
- From the Department of Radiology (M.W., Y.M., L.L., X.P., Y.W., Y.Q., D.G., D.T.), The First Hospital of Jilin University, Changchun, China
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Chen M, Guo Y, Wang P, Chen Q, Bai L, Wang S, Su Y, Wang L, Gong G. An Effective Approach to Improve the Automatic Segmentation and Classification Accuracy of Brain Metastasis by Combining Multi-phase Delay Enhanced MR Images. J Digit Imaging 2023; 36:1782-1793. [PMID: 37259008 PMCID: PMC10406988 DOI: 10.1007/s10278-023-00856-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2023] [Revised: 05/16/2023] [Accepted: 05/18/2023] [Indexed: 06/02/2023] Open
Abstract
The objective of this study is to analyse the diffusion rule of the contrast media in multi-phase delayed enhanced magnetic resonance (MR) T1 images using radiomics and to construct an automatic classification and segmentation model of brain metastases (BM) based on support vector machine (SVM) and Dpn-UNet. A total of 189 BM patients with 1047 metastases were enrolled. Contrast-enhanced MR images were obtained at 1, 3, 5, 10, 18, and 20 min following contrast medium injection. The tumour target volume was delineated, and the radiomics features were extracted and analysed. BM segmentation and classification models in the MR images with different enhancement phases were constructed using Dpn-UNet and SVM, and differences in the BM segmentation and classification models with different enhancement times were compared. (1) The signal intensity for BM decreased with time delay and peaked at 3 min. (2) Among the 144 optimal radiomics features, 22 showed strong correlation with time (highest R-value = 0.82), while 41 showed strong correlation with volume (highest R-value = 0.99). (3) The average dice similarity coefficients of both the training and test sets were the highest at 10 min for the automatic segmentation of BM, reaching 0.92 and 0.82, respectively. (4) The areas under the curve (AUCs) for the classification of BM pathology type applying single-phase MRI was the highest at 10 min, reaching 0.674. The AUC for the classification of BM by applying the six-phase image combination was the highest, reaching 0.9596, and improved by 42.3% compared with that by applying single-phase images at 10 min. The dynamic changes of contrast media diffusion in BM can be reflected by multi-phase delayed enhancement based on radiomics, which can more objectively reflect the pathological types and significantly improve the accuracy of BM segmentation and classification.
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Affiliation(s)
- Mingming Chen
- Department of Radiation Physics, Shandong First Medical University Affiliated Cancer Hospital, Shandong Cancer Hospital and Institute (Shandong Cancer Hospital), Jinan, 250117, China
- College of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, 250117, China
| | - Yujie Guo
- Department of Radiation Physics, Shandong First Medical University Affiliated Cancer Hospital, Shandong Cancer Hospital and Institute (Shandong Cancer Hospital), Jinan, 250117, China
| | - Pengcheng Wang
- College of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, 250117, China
| | - Qi Chen
- MedMind Technology Co., Ltd, 100084, Beijing, China
| | - Lu Bai
- MedMind Technology Co., Ltd, 100084, Beijing, China
| | - Shaobin Wang
- MedMind Technology Co., Ltd, 100084, Beijing, China
| | - Ya Su
- Department of Radiation Physics, Shandong First Medical University Affiliated Cancer Hospital, Shandong Cancer Hospital and Institute (Shandong Cancer Hospital), Jinan, 250117, China
| | - Lizhen Wang
- Department of Radiation Physics, Shandong First Medical University Affiliated Cancer Hospital, Shandong Cancer Hospital and Institute (Shandong Cancer Hospital), Jinan, 250117, China
| | - Guanzhong Gong
- Department of Radiation Physics, Shandong First Medical University Affiliated Cancer Hospital, Shandong Cancer Hospital and Institute (Shandong Cancer Hospital), Jinan, 250117, China.
- Department of Engineering Physics, Tsing Hua University, Beijing, 100084, China.
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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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Huh H, Lee EH, Oh SS, Kim JH, Seo YB, Choo YJ, Park J, Chang MC. The blood-brain barrier disruption after syncope: a dynamic contrast-enhanced magnetic resonance imaging study: A case report. Medicine (Baltimore) 2021; 100:e28258. [PMID: 34918695 PMCID: PMC8677986 DOI: 10.1097/md.0000000000028258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Accepted: 11/25/2021] [Indexed: 01/05/2023] Open
Abstract
RATIONALE Using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), we demonstrated blood-brain barrier (BBB) disruption following syncope. PATIENT CONCERNS A 45-year-old man experienced syncope with a chief complaint of syncope (duration: 1 minutes), 1 day before visiting a university hospital for examination. He had no history of medical problems and was not taking any medications. This episode was the first in his lifetime. DIAGNOSES After syncope, the patient did not have any illnesses or symptoms, such as headache, cognitive deficits, or somnolence. INTERVENTIONS Cardiac evaluation did not reveal any abnormal findings. In addition, in conventional brain and chest computed tomography and brain MRI, no abnormal lesions were observed. OUTCOMES DCE-MRI of the patient showed bright blue colored lines within the sulci throughout the cerebral cortex. The regions of interest, including bright blue colored lines, had significantly higher Ktrans values (6.86 times higher) than those in healthy control participants. These findings are indicative of BBB disruption of the vessels in the sulci. LESSONS Using DCE-MRI, we demonstrated BBB disruption following syncope. DCE-MRI is a useful tool for the detection of BBB disruption following syncope.
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Affiliation(s)
- Hyungkyu Huh
- Medical Interdisciplinary Team, Medical Device Development Center, Daegu-Gyeongbuk Medical Innovation Foundation, Daegu, Korea
| | - Eun-Hee Lee
- Medical Interdisciplinary Team, Medical Device Development Center, Daegu-Gyeongbuk Medical Innovation Foundation, Daegu, Korea
| | - Sung Suk Oh
- Medical Interdisciplinary Team, Medical Device Development Center, Daegu-Gyeongbuk Medical Innovation Foundation, Daegu, Korea
| | - Jong-Hoon Kim
- Department of Neurosurgery, College of Medicine, Yeungnam University, Namku, Daegu, Republic of Korea
| | - Young Beom Seo
- Department of Neurosurgery, College of Medicine, Yeungnam University, Namku, Daegu, Republic of Korea
| | - Yoo Jin Choo
- Medical Interdisciplinary Team, Medical Device Development Center, Daegu-Gyeongbuk Medical Innovation Foundation, Daegu, Korea
| | - Juyoung Park
- Department of High-tech medical device, Gachon University, Seongnam, Republic of Korea
- SonoTx, Seongnam, Republic of Korea
| | - Min Cheol Chang
- Department of Physical Medicine & Rehabilitation, College of Medicine, Yeungnam University, Namku, Daegu, Republic of Korea
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Oh SS, Lee EH, Kim JH, Seo YB, Choo YJ, Park J, Chang MC. The Use of Dynamic Contrast-Enhanced Magnetic Resonance Imaging for the Evaluation of Blood-Brain Barrier Disruption in Traumatic Brain Injury: What Is the Evidence? Brain Sci 2021; 11:brainsci11060775. [PMID: 34208047 PMCID: PMC8230721 DOI: 10.3390/brainsci11060775] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Revised: 06/08/2021] [Accepted: 06/09/2021] [Indexed: 11/16/2022] Open
Abstract
(1) Background: Blood brain barrier (BBB) disruption following traumatic brain injury (TBI) results in a secondary injury by facilitating the entry of neurotoxins to the brain parenchyma without filtration. In the current paper, we aimed to review previous dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) studies to evaluate the occurrence of BBB disruption after TBI. (2) Methods: In electronic databases (PubMed, Scopus, Embase, and the Cochrane Library), we searched for the following keywords: dynamic contrast-enhanced OR DCE AND brain injury. We included studies in which BBB disruption was evaluated in patients with TBI using DCE-MRI. (3) Results: Four articles were included in this review. To assess BBB disruption, linear fit, Tofts, extended Tofts, or Patlak models were used. KTrans and ve were increased, and the values of vp were decreased in the cerebral cortex and predilection sites for diffusion axonal injury. These findings are indicative of BBB disruption following TBI. (4) Conclusions: Our analysis supports the possibility of utilizing DCE-MRI for the detection of BBB disruption following TBI.
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Affiliation(s)
- Sung Suk Oh
- Medical Interdisciplinary Team, Medical Device Development Center, Daegu-Gyeongbuk Medical Innovation Foundation, Daegu 41061, Korea; (S.S.O.); (E.-H.L.); (Y.J.C.)
| | - Eun-Hee Lee
- Medical Interdisciplinary Team, Medical Device Development Center, Daegu-Gyeongbuk Medical Innovation Foundation, Daegu 41061, Korea; (S.S.O.); (E.-H.L.); (Y.J.C.)
| | - Jong-Hoon Kim
- Department of Neurosurgery, College of Medicine, Yeungnam University, Daegu 41061, Korea; (J.-H.K.); (Y.B.S.)
| | - Young Beom Seo
- Department of Neurosurgery, College of Medicine, Yeungnam University, Daegu 41061, Korea; (J.-H.K.); (Y.B.S.)
| | - Yoo Jin Choo
- Medical Interdisciplinary Team, Medical Device Development Center, Daegu-Gyeongbuk Medical Innovation Foundation, Daegu 41061, Korea; (S.S.O.); (E.-H.L.); (Y.J.C.)
| | - Juyoung Park
- Medical Interdisciplinary Team, Medical Device Development Center, Daegu-Gyeongbuk Medical Innovation Foundation, Daegu 41061, Korea; (S.S.O.); (E.-H.L.); (Y.J.C.)
- Correspondence: (J.P.); (M.C.C.)
| | - Min Cheol Chang
- Department of Rehabilitation Medicine, College of Medicine, Yeungnam University, Daegu 41061, Korea
- Correspondence: (J.P.); (M.C.C.)
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