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Ghasemi A, Ahlawat S, Fayad LM. Magnetic Resonance Imaging Biomarkers of Bone and Soft Tissue Tumors. Semin Musculoskelet Radiol 2024; 28:39-48. [PMID: 38330969 DOI: 10.1055/s-0043-1776433] [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: 02/10/2024]
Abstract
Magnetic resonance imaging (MRI) is essential in the management of musculoskeletal (MSK) tumors. This review delves into the diverse MRI modalities, focusing on anatomical, functional, and metabolic sequences that provide essential biomarkers for tumor detection, characterization, disease extent determination, and assessment of treatment response. MRI's multimodal capabilities offer a range of biomarkers that enhance MSK tumor evaluation, aiding in better patient management.
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Affiliation(s)
- Ali Ghasemi
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins Medical Institutions, Baltimore, Maryland
| | - Shivani Ahlawat
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins Medical Institutions, Baltimore, Maryland
| | - Laura Marie Fayad
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins Medical Institutions, Baltimore, Maryland
- Department of Orthopaedic Surgery, Johns Hopkins University School of Medicine, Baltimore, Maryland
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland
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Deng X, Duan Z, Fang S, Wang S. Advances in The Application and Research of Magnetic Resonance Diffusion Kurtosis Imaging in The Musculoskeletal System. J Magn Reson Imaging 2023; 57:670-689. [PMID: 36200754 DOI: 10.1002/jmri.28463] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 09/22/2022] [Accepted: 09/22/2022] [Indexed: 11/11/2022] Open
Abstract
Magnetic resonance diffusion kurtosis imaging (DKI) is an emerging magnetic resonance imaging (MRI) technique that can reflect microstructural changes in tissue through non-Gaussian diffusion of water molecules. Compared to traditional diffusion weighted imaging (DWI), the DKI model has shown greater sensitivity for diagnosis of musculoskeletal diseases and can help formulate more reasonable treatment plans. Moreover, DKI is an important auxiliary examination for evaluation of the motor function of the musculoskeletal system. This article briefly introduces the basic principles of DKI and reviews the application and research of DKI in the evaluation of disorders of the musculoskeletal system (including bone tumors, soft tissue tumors, spinal lesions, chronic musculoskeletal diseases, musculoskeletal trauma, and developmental disorders) as well as the normal musculoskeletal tissues. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: 1.
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Affiliation(s)
- Xiyang Deng
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian, China
| | - Zhiqing Duan
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian, China
| | - Shaobo Fang
- Department of Medical Imaging, Zhengzhou University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, Henan, China.,Academy of Medical Sciences, Zhengzhou University, Zhengzhou, Henan, China
| | - Shaowu Wang
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian, China
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Chatziantoniou C, Schoot RA, van Ewijk R, van Rijn RR, ter Horst SAJ, Merks JHM, Leemans A, De Luca A. Methodological considerations on segmenting rhabdomyosarcoma with diffusion-weighted imaging-What can we do better? Insights Imaging 2023; 14:19. [PMID: 36720720 PMCID: PMC9889596 DOI: 10.1186/s13244-022-01351-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 12/04/2022] [Indexed: 02/02/2023] Open
Abstract
PURPOSE Diffusion-weighted MRI is a promising technique to monitor response to treatment in pediatric rhabdomyosarcoma. However, its validation in clinical practice remains challenging. This study aims to investigate how the tumor segmentation strategy can affect the apparent diffusion coefficient (ADC) measured in pediatric rhabdomyosarcoma. MATERIALS AND METHODS A literature review was performed in PubMed using search terms relating to MRI and sarcomas to identify commonly applied segmentation strategies. Seventy-six articles were included, and their presented segmentation methods were evaluated. Commonly reported segmentation strategies were then evaluated on diffusion-weighted imaging of five pediatric rhabdomyosarcoma patients to assess their impact on ADC. RESULTS We found that studies applied different segmentation strategies to define the shape of the region of interest (ROI)(outline 60%, circular ROI 27%), to define the segmentation volume (2D 44%, multislice 9%, 3D 21%), and to define the segmentation area (excludes edge 7%, excludes other region 19%, specific area 27%, whole tumor 48%). In addition, details of the segmentation strategy are often unreported. When implementing and comparing these strategies on in-house data, we found that excluding necrotic, cystic, and hemorrhagic areas from segmentations resulted in on average 5.6% lower mean ADC. Additionally, the slice location used in 2D segmentation methods could affect ADC by as much as 66%. CONCLUSION Diffusion-weighted MRI studies in pediatric sarcoma currently employ a variety of segmentation methods. Our study shows that different segmentation strategies can result in vastly different ADC measurements, highlighting the importance to further investigate and standardize segmentation.
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Affiliation(s)
- Cyrano Chatziantoniou
- grid.7692.a0000000090126352Image Sciences Institute, UMC Utrecht, Utrecht, The Netherlands ,grid.487647.ePrincess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands
| | - Reineke A. Schoot
- grid.487647.ePrincess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands
| | - Roelof van Ewijk
- grid.487647.ePrincess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands
| | - Rick R. van Rijn
- grid.7177.60000000084992262Department of Radiology and Nuclear Medicine, Amsterdam UMC Location University of Amsterdam, Amsterdam, The Netherlands
| | - Simone A. J. ter Horst
- grid.487647.ePrincess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands ,grid.417100.30000 0004 0620 3132Department of Radiology and Nuclear Medicine, Wilhelmina Children’s Hospital UMC Utrecht, Utrecht, The Netherlands
| | - Johannes H. M. Merks
- grid.487647.ePrincess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands
| | - Alexander Leemans
- grid.7692.a0000000090126352Image Sciences Institute, UMC Utrecht, Utrecht, The Netherlands
| | - Alberto De Luca
- grid.7692.a0000000090126352Image Sciences Institute, UMC Utrecht, Utrecht, The Netherlands ,grid.7692.a0000000090126352Department of Neurology, UMC Utrecht Brain Center, UMCUtrecht, Utrecht, The Netherlands
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Soft Tissue Sarcomas: The Role of Quantitative MRI in Treatment Response Evaluation. Acad Radiol 2022; 29:1065-1084. [PMID: 34548230 DOI: 10.1016/j.acra.2021.08.007] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 07/29/2021] [Accepted: 08/12/2021] [Indexed: 12/12/2022]
Abstract
BACKGROUND Although curative surgery remains the cornerstone of the therapeutic strategy in patients with soft tissue sarcomas (STS), neoadjuvant radiotherapy and chemotherapy (NART and NACT, respectively) are increasingly used to improve operability, surgical margins and patient outcome. The best imaging modality for locoregional assessment of STS is MRI but these tumors are mostly evaluated in a qualitative manner. OBJECTIVE After an overview of the current standard of care regarding treatment for patients with locally advanced STS, this review aims to summarize the principles and limitations of (i) the current methods used to evaluate response to neoadjuvant treatment in clinical practice and clinical trials in STS (RECIST 1.1 and modified Choi criteria), (ii) quantitative MRI sequences (i.e., diffusion weighted imaging and dynamic contrast enhanced MRI), and (iii) texture analyses and (delta-) radiomics.
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Zhang K, Dai Y, Liu Y, Tao J, Pan Z, Xie L, Wang S. Soft tissue sarcoma: IVIM and DKI parameters correlate with Ki-67 labeling index on direct comparison of MRI and histopathological slices. Eur Radiol 2022; 32:5659-5668. [DOI: 10.1007/s00330-022-08646-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Revised: 01/28/2022] [Accepted: 02/11/2022] [Indexed: 12/27/2022]
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Bajaj G, Callan AK, Weinschenk RC, Chhabra A. Multiparametric Evaluation of Soft Tissue Sarcoma: Current Perspectives and Future Directions. Semin Roentgenol 2022; 57:212-231. [DOI: 10.1053/j.ro.2022.02.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 01/31/2022] [Accepted: 02/02/2022] [Indexed: 11/11/2022]
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Fang S, Yang Y, Xu N, Tu Y, Yin Z, Zhang Y, Liu Y, Duan Z, Liu W, Wang S. An Update in Imaging Evaluation of Histopathological Grade of Soft Tissue Sarcomas Using Structural and Quantitative Imaging and Radiomics. J Magn Reson Imaging 2021; 55:1357-1375. [PMID: 34637568 DOI: 10.1002/jmri.27954] [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: 08/03/2021] [Revised: 09/28/2021] [Accepted: 09/30/2021] [Indexed: 12/22/2022] Open
Abstract
Over the past two decades, considerable efforts have been made to develop non-invasive methods for determining tumor grade or surrogates for predicting the biological behavior, aiding early treatment decisions, and providing prognostic information. The development of new imaging tools, such as diffusion-weighted imaging, diffusion kurtosis imaging, perfusion imaging, and magnetic resonance spectroscopy have provided leverage in the diagnosis of soft tissue sarcomas. Artificial intelligence is a new technology used to study and simulate human thinking and abilities, which can extract and analyze advanced and quantitative image features from medical images with high throughput for an in-depth characterization of the spatial heterogeneity of tumor tissues. This article reviews the current imaging modalities used to predict the histopathological grade of soft tissue sarcomas and highlights the advantages and limitations of each modality. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Shaobo Fang
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian, China
| | - Yanyu Yang
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian, China
| | - Nan Xu
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian, China
| | - Yun Tu
- Department of Radiology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China
| | - Zhenzhen Yin
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian, China
| | - Yu Zhang
- Department of Medical Imaging, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, Shenyang, China
| | - Yajie Liu
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian, China
| | - Zhiqing Duan
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian, China
| | - Wenyu Liu
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian, China
| | - Shaowu Wang
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian, China
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