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Yan Q, Yan X, Yang X, Li S, Song J. The use of PET/MRI in radiotherapy. Insights Imaging 2024; 15:63. [PMID: 38411742 PMCID: PMC10899128 DOI: 10.1186/s13244-024-01627-6] [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: 09/19/2023] [Accepted: 01/21/2024] [Indexed: 02/28/2024] Open
Abstract
Positron emission tomography/magnetic resonance imaging (PET/MRI) is a hybrid imaging technique that quantitatively combines the metabolic and functional data from positron emission tomography (PET) with anatomical and physiological information from MRI. As PET/MRI technology has advanced, its applications in cancer care have expanded. Recent studies have demonstrated that PET/MRI provides unique advantages in the field of radiotherapy and has become invaluable in guiding precision radiotherapy techniques. This review discusses the rationale and clinical evidence supporting the use of PET/MRI for radiation positioning, target delineation, efficacy evaluation, and patient surveillance.Critical relevance statement This article critically assesses the transformative role of PET/MRI in advancing precision radiotherapy, providing essential insights into improved radiation positioning, target delineation, efficacy evaluation, and patient surveillance in clinical radiology practice.Key points• The emergence of PET/MRI will be a key bridge for precise radiotherapy.• PET/MRI has unique advantages in the whole process of radiotherapy.• New tracers and nanoparticle probes will broaden the use of PET/MRI in radiation.• PET/MRI will be utilized more frequently for radiotherapy.
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Affiliation(s)
- Qi Yan
- Cancer Center, Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences Tongji Shanxi Hospital, Taiyuan, China
| | - Xia Yan
- Cancer Center, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, China
- Shanxi Provincial Key Laboratory for Translational Nuclear Medicine and Precision Protection, Taiyuan, China
| | - Xin Yang
- Cancer Center, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, China
| | - Sijin Li
- Department of Nuclear Medicine, First Hospital of Shanxi Medical University, Shanxi Medical University, Taiyuan, China.
| | - Jianbo Song
- Cancer Center, Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences Tongji Shanxi Hospital, Taiyuan, China.
- Shanxi Provincial Key Laboratory for Translational Nuclear Medicine and Precision Protection, Taiyuan, China.
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Yoon J, Baek N, Yoo RE, Choi SH, Kim TM, Park CK, Park SH, Won JK, Lee JH, Lee ST, Choi KS, Lee JY, Hwang I, Kang KM, Yun TJ. Added value of dynamic contrast-enhanced MR imaging in deep learning-based prediction of local recurrence in grade 4 adult-type diffuse gliomas patients. Sci Rep 2024; 14:2171. [PMID: 38273075 PMCID: PMC10810891 DOI: 10.1038/s41598-024-52841-7] [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: 08/25/2023] [Accepted: 01/24/2024] [Indexed: 01/27/2024] Open
Abstract
Local recurrences in patients with grade 4 adult-type diffuse gliomas mostly occur within residual non-enhancing T2 hyperintensity areas after surgical resection. Unfortunately, it is challenging to distinguish non-enhancing tumors from edema in the non-enhancing T2 hyperintensity areas using conventional MRI alone. Quantitative DCE MRI parameters such as Ktrans and Ve convey permeability information of glioblastomas that cannot be provided by conventional MRI. We used the publicly available nnU-Net to train a deep learning model that incorporated both conventional and DCE MRI to detect the subtle difference in vessel leakiness due to neoangiogenesis between the non-recurrence area and the local recurrence area, which contains a higher proportion of high-grade glioma cells. We found that the addition of Ve doubled the sensitivity while nonsignificantly decreasing the specificity for prediction of local recurrence in glioblastomas, which implies that the combined model may result in fewer missed cases of local recurrence. The deep learning model predictive of local recurrence may enable risk-adapted radiotherapy planning in patients with grade 4 adult-type diffuse gliomas.
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Affiliation(s)
- Jungbin Yoon
- Department of Radiology, Seoul National University College of Medicine, 101, Daehangno, Jongno-gu, Seoul, 03080, Republic of Korea
| | - Nayeon Baek
- Department of Radiology, Seoul National University College of Medicine, 101, Daehangno, Jongno-gu, Seoul, 03080, Republic of Korea
| | - Roh-Eul Yoo
- Department of Radiology, Seoul National University College of Medicine, 101, Daehangno, Jongno-gu, Seoul, 03080, Republic of Korea.
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea.
| | - Seung Hong Choi
- Department of Radiology, Seoul National University College of Medicine, 101, Daehangno, Jongno-gu, Seoul, 03080, Republic of Korea.
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea.
- Center for Nanoparticle Research, Institute for Basic Science (IBS), Seoul, Republic of Korea.
- School of Chemical and Biological Engineering, Seoul National University, 1, Gwanak-ro, Gwanak-gu, Seoul, 302-909, Republic of Korea.
| | - Tae Min Kim
- Department of Internal Medicine, Cancer Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Chul-Kee Park
- Department of Neurosurgery, Biomedical Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Sung-Hye Park
- Department of Pathology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Jae-Kyung Won
- Department of Pathology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Joo Ho Lee
- Department of Radiation Oncology, Cancer Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Soon Tae Lee
- Department of Neurology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Kyu Sung Choi
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Ji Ye Lee
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Inpyeong Hwang
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Koung Mi Kang
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Tae Jin Yun
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
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Xiong M, Chen Z, Zhou C, Yang X, Hu W, Jiang Y, Zheng R, Fan W, Mou Y, Lin X. PSMA PET/MR is a New Imaging Option for Identifying Glioma Recurrence and Predicting Prognosis. Recent Pat Anticancer Drug Discov 2024; 19:383-395. [PMID: 38214322 DOI: 10.2174/1574892818666230519150401] [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: 03/04/2023] [Revised: 04/05/2023] [Accepted: 04/11/2023] [Indexed: 01/13/2024]
Abstract
BACKGROUND Glioma is characterized by a high recurrence rate, while the results of the traditional imaging methods (including magnetic resonance imaging, MRI) to distinguish recurrence from treatment-related changes (TRCs) are poor. Prostate-specific membrane antigen (PSMA) (US10815200B2, Deutsches Krebsforschungszentrum, German Cancer Research Center) is a type II transmembrane glycoprotein overexpressed in glioma vascular endothelium, and it is a promising target for imaging and therapy. OBJECTIVE The study aimed to assess the performance of PSMA positron emission tomography/ magnetic resonance (PET/MR) for diagnosing recurrence and predicting prognosis in glioma patients. MATERIALS AND METHODS Patients suspected of glioma recurrence who underwent 18F-PSMA-1007 PET/MR were prospectively enrolled. Eight metabolic parameters and fifteen texture features of the lesion were extracted from PSMA PET/MR. The ability of PSMA PET/MR to diagnose glioma recurrence was investigated and compared with conventional MRI. The diagnostic agreement was assessed using Cohen κ scores and the predictive parameters of PSMA PET/MR were obtained. Kaplan-Meier method and Cox proportional hazard model were used to analyze recurrence- free survival (RFS) and overall survival (OS). Finally, the expression of PSMA was analyzed by immunohistochemistry (IHC). RESULTS Nineteen patients with a mean age of 48.11±15.72 were assessed. The maximum tumorto- parotid ratio (TPRmax) and texture features extracted from PET and T1-weighted contrast enhancement (T1-CE) MR showed differences between recurrence and TRCs (all p <0.05). PSMA PET/MR and conventional MRI exhibited comparable power in diagnosing recurrence with specificity and PPV of 100%. The interobserver concordance was fair between the two modalities (κ = 0.542, p = 0.072). The optimal cutoffs of metabolic parameters, including standardized uptake value (SUV, SUVmax, SUVmean, and SUVpeak) and TPRmax for predicting recurrence were 3.35, 1.73, 1.99, and 0.17 respectively, with the area under the curve (AUC) ranging from 0.767 to 0.817 (all p <0.05). In grade 4 glioblastoma (GBM) patients, SUVmax, SUVmean, SUVpeak, TBRmax, TBRmean, and TPRmax showed improved performance of AUC (0.833-0.867, p <0.05). Patients with SUVmax, SUVmean, or SUVpeak more than the cutoff value had significantly shorter RFS (all p <0.05). In addition, patients with SUVmean, SUVpeak, or TPRmax more than the cutoff value had significantly shorter OS (all p <0.05). PSMA expression of glioma vascular endothelium was observed in ten (10/11, 90.9%) patients with moderate-to-high levels in all GBM cases (n = 6/6, 100%). CONCLUSION This primitive study shows multiparameter PSMA PET/MR to be useful in identifying glioma (especially GBM) recurrence by providing excellent tumor background comparison, tumor heterogeneity, recurrence prediction and prognosis information, although it did not improve the diagnostic performance compared to conventional MRI. Further and larger studies are required to define its potential clinical application in this setting.
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Affiliation(s)
- Min Xiong
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Nuclear Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Zhenghe Chen
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Neurosurgery/Neuro-oncology, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Chao Zhou
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Nuclear Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Xiaochun Yang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Nuclear Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Wanming Hu
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Pathology, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Yongluo Jiang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Nuclear Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Rongliang Zheng
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Nuclear Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Wei Fan
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Nuclear Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Yonggao Mou
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Neurosurgery/Neuro-oncology, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Xiaoping Lin
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Nuclear Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
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4
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Lau KS, Ruisi I, Back M. Association of MRI Volume Parameters in Predicting Patient Outcome at Time of Initial Diagnosis of Glioblastoma. Brain Sci 2023; 13:1579. [PMID: 38002539 PMCID: PMC10670247 DOI: 10.3390/brainsci13111579] [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: 09/29/2023] [Revised: 11/08/2023] [Accepted: 11/09/2023] [Indexed: 11/26/2023] Open
Abstract
PURPOSE Patients with glioblastoma (GBM) may demonstrate varying patterns of infiltration and relapse. Improving the ability to predict these patterns may influence the management strategies at the time of initial diagnosis. This study aims to examine the impact of the ratio (T2/T1) of the non-enhancing volume in T2-weighted images (T2) to the enhancing volume in MRI T1-weighted gadolinium-enhanced images (T1gad) on patient outcome. METHODS AND MATERIALS A retrospective audit was performed from established prospective databases in patients managed consecutively with radiation therapy (RT) for GBM between 2016 and 2019. Patient, tumour and treatment-related factors were assessed in relation to outcome. Volumetric data from the initial diagnostic MRI were obtained via the manual segmentation of the T1gd and T2 abnormalities. A T2/T1 ratio was calculated from these volumes. The initial relapse site was assessed on MRI in relation to the site of the original T1gad volume and surgical cavity. The major endpoints were median relapse-free survival (RFS) from the date of diagnosis and site of initial relapse (defined as either local at the initial surgical site or any distance more than 20 mm from initial T1gad abnormality). The analysis was performed for association between known prognostic factors as well as the radiological factors using log-rank tests for subgroup comparisons, with correction for multiple comparisons. RESULTS One hundred and seventy-seven patients with GBM were managed consecutively with RT between 2016 and 2019 and were eligible for the analysis. The median age was 62 years. Seventy-four percent were managed under a 60Gy (Stupp) protocol, whilst 26% were on a 40Gy (Elderly) protocol. Major neuroanatomical subsites were Lateral Temporal (18%), Anterior Temporal (13%) and Medial Frontal (10%). Median volumes on T1gd and T2 were 20 cm3 (q1-3:8-43) and 37 cm3 (q1-3: 17-70), respectively. The median T2/T1 ratio was 2.1. For the whole cohort, the median OS was 16.0 months (95%CI:14.1-18.0). One hundred and forty-eight patients have relapsed with a median RFS of 11.4 months (95%CI:10.4-12.5). A component of distant relapse was evident in 43.9% of relapses, with 23.6% isolated relapse. Better ECOG performance Status (p = 0.007), greater extent of resection (p = 0.020), MGMT methylation (p < 0.001) and RT60Gy Dose (p = 0.050) were associated with improved RFS. Although the continuous variable of initial T1gd volume (p = 0.39) and T2 volume (p = 0.23) were not associated with RFS, the lowest T2/T1 quartile (reflecting a relatively lower T2 volume compared to T1gd volume) was significantly associated with improved RFS (p = 0.016) compared with the highest quartile. The lowest T2/T1 ratio quartile was also associated with a lower risk of distant relapse (p = 0.031). CONCLUSION In patients diagnosed with GBM, the volumetric parameters of the diagnostic MRI with a ratio of T2 and T1gad abnormality may assist in the prediction of relapse-free survival and patterns of relapse. A further understanding of these relationships has the potential to impact the design of future radiation therapy target volume delineation protocols.
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Affiliation(s)
- Kin Sing Lau
- Department of Radiation Oncology, Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, NSW 2065, Australia;
- Central Coast Cancer Centre, Gosford Hospital, Gosford, NSW 2250, Australia
| | - Isidoro Ruisi
- Central Coast Cancer Centre, Gosford Hospital, Gosford, NSW 2250, Australia
| | - Michael Back
- Department of Radiation Oncology, Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, NSW 2065, Australia;
- Central Coast Cancer Centre, Gosford Hospital, Gosford, NSW 2250, Australia
- Genesis Care, Sydney, NSW 2015, Australia
- Sydney Medical School, University of Sydney, Sydney, NSW 2050, Australia
- The Brain Cancer Group, Sydney, NSW 2065, Australia
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5
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Heo D, Lee J, Yoo RE, Choi SH, Kim TM, Park CK, Park SH, Won JK, Lee JH, Lee ST, Choi KS, Lee JY, Hwang I, Kang KM, Yun TJ. Deep learning based on dynamic susceptibility contrast MR imaging for prediction of local progression in adult-type diffuse glioma (grade 4). Sci Rep 2023; 13:13864. [PMID: 37620555 PMCID: PMC10449894 DOI: 10.1038/s41598-023-41171-9] [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: 02/23/2023] [Accepted: 08/23/2023] [Indexed: 08/26/2023] Open
Abstract
Adult-type diffuse glioma (grade 4) has infiltrating nature, and therefore local progression is likely to occur within surrounding non-enhancing T2 hyperintense areas even after gross total resection of contrast-enhancing lesions. Cerebral blood volume (CBV) obtained from dynamic susceptibility contrast perfusion-weighted imaging (DSC-PWI) is a parameter that is well-known to be a surrogate marker of both histologic and angiographic vascularity in tumors. We built two nnU-Net deep learning models for prediction of early local progression in adult-type diffuse glioma (grade 4), one using conventional MRI alone and one using multiparametric MRI, including conventional MRI and DSC-PWI. Local progression areas were annotated in a non-enhancing T2 hyperintense lesion on preoperative T2 FLAIR images, using the follow-up contrast-enhanced (CE) T1-weighted (T1W) images as the reference standard. The sensitivity was doubled with the addition of nCBV (80% vs. 40%, P = 0.02) while the specificity was decreased nonsignificantly (29% vs. 48%, P = 0.39), suggesting that fewer cases of early local progression would be missed with the addition of nCBV. While the diagnostic performance of CBV model is still poor and needs improving, the multiparametric deep learning model, which presumably learned from the subtle difference in vascularity between early local progression and non-progression voxels within perilesional T2 hyperintensity, may facilitate risk-adapted radiotherapy planning in adult-type diffuse glioma (grade 4) patients.
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Affiliation(s)
- Donggeon Heo
- Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Jisoo Lee
- Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Roh-Eul Yoo
- Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea.
- Department of Radiology, Seoul National University Hospital, 101, Daehangno, Jongno-Gu, Seoul, 03080, Republic of Korea.
| | - Seung Hong Choi
- Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea.
- Department of Radiology, Seoul National University Hospital, 101, Daehangno, Jongno-Gu, Seoul, 03080, Republic of Korea.
- Center for Nanoparticle Research, Institute for Basic Science (IBS), Seoul, Republic of Korea.
- School of Chemical and Biological Engineering, Seoul National University, 1, Gwanak-Ro, Gwanak-Gu, Seoul, 302-909, Republic of Korea.
| | - Tae Min Kim
- Department of Internal Medicine, Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea
| | - Chul-Kee Park
- Department of Neurosurgery, Biomedical Research Institute, Seoul National University College of Medicine, Seoul, Korea
| | - Sung-Hye Park
- Department of Pathology, Seoul National University College of Medicine, Seoul, Korea
| | - Jae-Kyung Won
- Department of Pathology, Seoul National University College of Medicine, Seoul, Korea
| | - Joo Ho Lee
- Department of Radiation Oncology, Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea
| | - Soon Tae Lee
- Department of Neurology, Seoul National University College of Medicine, Seoul, Korea
| | - Kyu Sung Choi
- Department of Radiology, Seoul National University Hospital, 101, Daehangno, Jongno-Gu, Seoul, 03080, Republic of Korea
| | - Ji Ye Lee
- Department of Radiology, Seoul National University Hospital, 101, Daehangno, Jongno-Gu, Seoul, 03080, Republic of Korea
| | - Inpyeong Hwang
- Department of Radiology, Seoul National University Hospital, 101, Daehangno, Jongno-Gu, Seoul, 03080, Republic of Korea
| | - Koung Mi Kang
- Department of Radiology, Seoul National University Hospital, 101, Daehangno, Jongno-Gu, Seoul, 03080, Republic of Korea
| | - Tae Jin Yun
- Department of Radiology, Seoul National University Hospital, 101, Daehangno, Jongno-Gu, Seoul, 03080, Republic of Korea
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6
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Koh ES, Gan HK, Senko C, Francis RJ, Ebert M, Lee ST, Lau E, Khasraw M, Nowak AK, Bailey DL, Moffat BA, Fitt G, Hicks RJ, Coffey R, Verhaak R, Walsh KM, Barnes EH, De Abreu Lourenco R, Rosenthal M, Adda L, Foroudi F, Lasocki A, Moore A, Thomas PA, Roach P, Back M, Leonard R, Scott AM. [ 18F]-fluoroethyl-L-tyrosine (FET) in glioblastoma (FIG) TROG 18.06 study: protocol for a prospective, multicentre PET/CT trial. BMJ Open 2023; 13:e071327. [PMID: 37541751 PMCID: PMC10407346 DOI: 10.1136/bmjopen-2022-071327] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 07/08/2023] [Indexed: 08/06/2023] Open
Abstract
INTRODUCTION Glioblastoma is the most common aggressive primary central nervous system cancer in adults characterised by uniformly poor survival. Despite maximal safe resection and postoperative radiotherapy with concurrent and adjuvant temozolomide-based chemotherapy, tumours inevitably recur. Imaging with O-(2-[18F]-fluoroethyl)-L-tyrosine (FET) positron emission tomography (PET) has the potential to impact adjuvant radiotherapy (RT) planning, distinguish between treatment-induced pseudoprogression versus tumour progression as well as prognostication. METHODS AND ANALYSIS The FET-PET in Glioblastoma (FIG) study is a prospective, multicentre, non-randomised, phase II study across 10 Australian sites and will enrol up to 210 adults aged ≥18 years with newly diagnosed glioblastoma. FET-PET will be performed at up to three time points: (1) following initial surgery and prior to commencement of chemoradiation (FET-PET1); (2) 4 weeks following concurrent chemoradiation (FET-PET2); and (3) within 14 days of suspected clinical and/or radiological progression on MRI (performed at the time of clinical suspicion of tumour recurrence) (FET-PET3). The co-primary outcomes are: (1) to investigate how FET-PET versus standard MRI impacts RT volume delineation and (2) to determine the accuracy and management impact of FET-PET in distinguishing pseudoprogression from true tumour progression. The secondary outcomes are: (1) to investigate the relationships between FET-PET parameters (including dynamic uptake, tumour to background ratio, metabolic tumour volume) and progression-free survival and overall survival; (2) to assess the change in blood and tissue biomarkers determined by serum assay when comparing FET-PET data acquired prior to chemoradiation with other prognostic markers, looking at the relationships of FET-PET versus MRI-determined site/s of progressive disease post chemotherapy treatment with MRI and FET-PET imaging; and (3) to estimate the health economic impact of incorporating FET-PET into glioblastoma management and in the assessment of post-treatment pseudoprogression or recurrence/true progression. Exploratory outcomes include the correlation of multimodal imaging, blood and tumour biomarker analyses with patterns of failure and survival. ETHICS AND DISSEMINATION The study protocol V.2.0 dated 20 November 2020 has been approved by a lead Human Research Ethics Committee (Austin Health, Victoria). Other clinical sites will provide oversight through local governance processes, including obtaining informed consent from suitable participants. The study will be conducted in accordance with the principles of the Declaration of Helsinki and Good Clinical Practice. Results of the FIG study (TROG 18.06) will be disseminated via relevant scientific and consumer forums and peer-reviewed publications. TRIAL REGISTRATION NUMBER ANZCTR ACTRN12619001735145.
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Affiliation(s)
- Eng-Siew Koh
- Radiation Oncology, Liverpool Hospital, Liverpool, New South Wales, Australia
- South West Sydney Clinical School, University of New South Wales, Sydney, New South Wales, Australia
| | - Hui K Gan
- Austin Health, Department of Medical Oncology, Melbourne, Victoria, Australia
- School of Cancer Medicine, La Trobe University, Melbourne, Victoria, Australia
- Tumour Targeting Program, Olivia Newton-John Cancer Research Institute, Heidelberg, Victoria, Australia
- School of Medicine, University of Melbourne, Melbourne, Victoria, Australia
| | - Clare Senko
- School of Cancer Medicine, La Trobe University, Melbourne, Victoria, Australia
- Tumour Targeting Program, Olivia Newton-John Cancer Research Institute, Heidelberg, Victoria, Australia
- Department of Molecular Imaging and Therapy, Austin Health, Heidelberg, Victoria, Australia
| | - Roslyn J Francis
- Department of Nuclear Medicine, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
- Medical School, The University of Western Australia, Crawley, Western Australia, Australia
| | - Martin Ebert
- Department of Radiation Oncology, Sir Charles Gairdner Hospital, Perth, Western Australia, Australia
- School of Physics, Mathematics and Computing, University of Western Australia, Crawley, Western Australia, Australia
| | - Sze Ting Lee
- School of Cancer Medicine, La Trobe University, Melbourne, Victoria, Australia
- Tumour Targeting Program, Olivia Newton-John Cancer Research Institute, Heidelberg, Victoria, Australia
- School of Medicine, University of Melbourne, Melbourne, Victoria, Australia
- Department of Molecular Imaging and Therapy, Austin Health, Heidelberg, Victoria, Australia
| | - Eddie Lau
- Department of Molecular Imaging and Therapy, Austin Health, Heidelberg, Victoria, Australia
- Department of Radiology, University of Melbourne, Melbourne, Victoria, Australia
- Department of Radiology, Austin Health, Heidelberg, Victoria, Australia
| | - Mustafa Khasraw
- Department of Neurosurgery and Preston Robert Tisch Brain Tumor Center, Duke University School of Medicine, Durham, North Carolina, USA
| | - Anna K Nowak
- Medical School, The University of Western Australia, Crawley, Western Australia, Australia
- Department of Medical Oncology, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
| | - Dale L Bailey
- Faculty of Medicine & Health, University of Sydney, Camperdown, New South Wales, Australia
- Department of Nuclear Medicine, Royal North Shore Hospital, St Leonards, New South Wales, Australia
| | - Bradford A Moffat
- Melbourne Brain Centre Imaging Unit, Department of Radiology, University of Melbourne, Melbourne, Victoria, Australia
| | - Greg Fitt
- Department of Radiology, University of Melbourne, Melbourne, Victoria, Australia
- Department of Radiology, Austin Health, Heidelberg, Victoria, Australia
| | - Rodney J Hicks
- Department of Radiology, University of Melbourne, Melbourne, Victoria, Australia
- Centre for Cancer Imaging, Peter MacCallum Cancer Centre, East Melbourne, Victoria, Australia
| | - Robert Coffey
- Epithelial Biology Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Roel Verhaak
- Department of Neurosurgery, Yale School of Medicine, New Haven, Connecticut, USA
- Department of Neurosurgery, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Kyle M Walsh
- Department of Neurosurgery and Preston Robert Tisch Brain Tumor Center, Duke University School of Medicine, Durham, North Carolina, USA
| | - Elizabeth H Barnes
- NHMRC Clinical Trials Centre, The University of Sydney, Sydney, New South Wales, Australia
| | - Richard De Abreu Lourenco
- Centre for Health Economics Research and Evaluation, University of Technology Sydney, Broadway, New South Wales, Australia
| | - Mark Rosenthal
- School of Medicine, University of Melbourne, Melbourne, Victoria, Australia
- Department of Medical Oncology, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Lucas Adda
- The Cooperative Trials Group for Neuro-Oncology (COGNO) Consumer Advisor Panel, National Health and Medical Research Council (NHMRC) Clinical Trials Centre (CTC), University of Sydney, Sydney, New South Wales, Australia
| | - Farshad Foroudi
- School of Cancer Medicine, La Trobe University, Melbourne, Victoria, Australia
- Department of Radiation Oncology, Austin Health, Melbourne, Victoria, Australia
| | - Arian Lasocki
- Department of Cancer Imaging, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia
| | - Alisha Moore
- Trans Tasman Radiation Oncology Group (TROG), Newcastle, New South Wales, Australia
| | - Paul A Thomas
- Department of Nuclear Medicine, Royal Brisbane and Women's Hospital, Brisbane, Queensland, Australia
- Faculty of Medicine, The University of Queensland, Saint Lucia, Queensland, Australia
| | - Paul Roach
- Department of Nuclear Medicine, Royal North Shore Hospital, St Leonards, New South Wales, Australia
- The University of Sydney, Camperdown, New South Wales, Australia
| | - Michael Back
- Department of Radiation Oncology, Royal North Shore Hospital, St Leonards, New South Wales, Australia
- Faculty of Medicine & Health, University of Sydney, Sydney, New South Wales, Australia
| | - Robyn Leonard
- NHMRC Clinical Trials Centre, The University of Sydney, Sydney, New South Wales, Australia
| | - Andrew M Scott
- School of Cancer Medicine, La Trobe University, Melbourne, Victoria, Australia
- Tumour Targeting Program, Olivia Newton-John Cancer Research Institute, Heidelberg, Victoria, Australia
- School of Medicine, University of Melbourne, Melbourne, Victoria, Australia
- Department of Molecular Imaging and Therapy, Austin Health, Heidelberg, Victoria, Australia
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Darcourt J, Chardin D, Bourg V, Gal J, Schiappa R, Blonski M, Koulibaly PM, Almairac F, Mondot L, Le Jeune F, Collombier L, Kas A, Taillandier L, Verger A. Added value of [ 18F]FDOPA PET to the management of high-grade glioma patients after their initial treatment: a prospective multicentre study. Eur J Nucl Med Mol Imaging 2023; 50:2727-2735. [PMID: 37086272 DOI: 10.1007/s00259-023-06225-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Accepted: 04/04/2023] [Indexed: 04/23/2023]
Abstract
BACKGROUND Diagnostic value of 3,4-dihydroxy-6-[18F]fluoro-L-phenylalanine ([18F]FDOPA) PET in patients with suspected recurrent gliomas is recognised. We conducted a multicentre prospective study to assess its added value in the practical management of patients suspected of recurrence of high grade gliomas (HGG). METHODS Patients with a proven HGG (WHO grade III and IV) were referred to the multidisciplinary neuro-oncology board (MNOB) during their follow-up after initial standard of care treatment and when MRI findings were not fully conclusive. Each case was discussed in 2 steps. For step 1, a diagnosis and a management proposal were made only based on the clinical and the MRI data. For step 2, the same process was repeated taking the [18F]FDOPA PET results into consideration. A level of confidence for the decisions was assigned to each step. Changes in diagnosis and management induced by [18F]FDOPA PET information were measured. When unchanged, the difference in the confidence of the decisions were assessed. The diagnostic performances of each step were measured. RESULTS 107 patients underwent a total of 138 MNOB assessments. The proposed diagnosis changed between step 1 and step 2 in 37 cases (26.8%) and the proposed management changed in 31 cases (22.5%). When the management did not change, the confidence in the MNOB final decision was increased in 87 cases (81.3%). Step 1 had a sensitivity, specificity and accuracy of 83%, 58% and 66% and step 2, 86%, 64% and 71% respectively. CONCLUSION [18F]FDOPA PET adds significant information for the follow-up of HGG patients in clinical practice. When MRI findings are not straightforward, it can change the management for more than 20% of the patients and increases the confidence level of the multidisciplinary board decisions.
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Affiliation(s)
- Jacques Darcourt
- Department of Nuclear Medicine, Centre Antoine Lacassagne and UMR 4320 CEA-UCA, Université Côte d'Azur, Nice, France.
| | - David Chardin
- Department of Nuclear Medicine, Centre Antoine Lacassagne and UMR 4320 CEA-UCA, Université Côte d'Azur, Nice, France
| | - Véronique Bourg
- Department of Neurology, CHU, Nice, Université Cote d'Azur, Nice, France
| | - Jocelyn Gal
- Epidemiology and Biostatistics Department, Centre Antoine Lacassagne and Université Côte d'Azur, Nice, France
| | - Renaud Schiappa
- Epidemiology and Biostatistics Department, Centre Antoine Lacassagne and Université Côte d'Azur, Nice, France
| | - Marie Blonski
- Department of Neuro-Oncology, CHU, Nancy and CNRS, UMR 7039, Université de Lorraine, Nancy, France
| | - Pierre-Malick Koulibaly
- Department of Nuclear Medicine, Centre Antoine Lacassagne and UMR 4320 CEA-UCA, Université Côte d'Azur, Nice, France
| | - Fabien Almairac
- Department of Neurosurgery, CHU Nice and UR2CA Team PIN, Université Côte d'Azur, Nice, France
| | - Lydiane Mondot
- Department of Radiology, CHU Nice, Université Côte d'Azur, Nice, France
| | - Florence Le Jeune
- Department of Nuclear Medicine, Centre Eugène Marquis, Rennes and LTSI INSERM 1099, Université de Rennes 1, Rennes, France
| | - Laurent Collombier
- Department of Nuclear Medicine, CHU Nîmes, Université de Montpellier, Nîmes, France
| | - Aurélie Kas
- Department of Nuclear Medicine, AP-HP Hôpitaux Universitaires Pitié-Salpétrière Charles Foix and LIB INSERM U1146, Sorbonne University, Paris, France
| | - Luc Taillandier
- Department of Neuro-Oncology, CHU, Nancy and CNRS, UMR 7039, Université de Lorraine, Nancy, France
| | - Antoine Verger
- Department of Nuclear Medicine & Nancyclotep Imaging Platform, CHU Nancy and IADI INSERM UMR 1254, Université de Lorraine, Nancy, France
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8
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Henssen D, Leijten L, Meijer FJA, van der Kolk A, Arens AIJ, Ter Laan M, Smeenk RJ, Gijtenbeek A, van de Giessen EM, Tolboom N, Oprea-Lager DE, Smits M, Nagarajah J. Head-To-Head Comparison of PET and Perfusion Weighted MRI Techniques to Distinguish Treatment Related Abnormalities from Tumor Progression in Glioma. Cancers (Basel) 2023; 15:cancers15092631. [PMID: 37174097 PMCID: PMC10177124 DOI: 10.3390/cancers15092631] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 05/01/2023] [Accepted: 05/03/2023] [Indexed: 05/15/2023] Open
Abstract
The post-treatment imaging surveillance of gliomas is challenged by distinguishing tumor progression (TP) from treatment-related abnormalities (TRA). Sophisticated imaging techniques, such as perfusion-weighted magnetic resonance imaging (MRI PWI) and positron-emission tomography (PET) with a variety of radiotracers, have been suggested as being more reliable than standard imaging for distinguishing TP from TRA. However, it remains unclear if any technique holds diagnostic superiority. This meta-analysis provides a head-to-head comparison of the diagnostic accuracy of the aforementioned imaging techniques. Systematic literature searches on the use of PWI and PET imaging techniques were carried out in PubMed, Embase, the Cochrane Library, ClinicalTrials.gov and the reference lists of relevant papers. After the extraction of data on imaging technique specifications and diagnostic accuracy, a meta-analysis was carried out. The quality of the included papers was assessed using the QUADAS-2 checklist. Nineteen articles, totaling 697 treated patients with glioma (431 males; mean age ± standard deviation 50.5 ± 5.1 years) were included. The investigated PWI techniques included dynamic susceptibility contrast (DSC), dynamic contrast enhancement (DCE) and arterial spin labeling (ASL). The PET-tracers studied concerned [S-methyl-11C]methionine, 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG), O-(2-[18F]fluoroethyl)-L-tyrosine ([18F]FET) and 6-[18F]-fluoro-3,4-dihydroxy-L-phenylalanine ([18F]FDOPA). The meta-analysis of all data showed no diagnostic superior imaging technique. The included literature showed a low risk of bias. As no technique was found to be diagnostically superior, the local level of expertise is hypothesized to be the most important factor for diagnostically accurate results in post-treatment glioma patients regarding the distinction of TRA from TP.
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Affiliation(s)
- Dylan Henssen
- Department of Medical Imaging, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
- Radboudumc Center of Expertise Neuro-Oncology, 6525 GA Nijmegen, The Netherlands
| | - Lars Leijten
- Department of Medical Imaging, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Frederick J A Meijer
- Department of Medical Imaging, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
- Radboudumc Center of Expertise Neuro-Oncology, 6525 GA Nijmegen, The Netherlands
| | - Anja van der Kolk
- Department of Medical Imaging, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
- Radboudumc Center of Expertise Neuro-Oncology, 6525 GA Nijmegen, The Netherlands
- Department of Radiology and Nuclear Medicine, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
| | - Anne I J Arens
- Department of Medical Imaging, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Mark Ter Laan
- Radboudumc Center of Expertise Neuro-Oncology, 6525 GA Nijmegen, The Netherlands
- Department of Neurosurgery, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Robert J Smeenk
- Radboudumc Center of Expertise Neuro-Oncology, 6525 GA Nijmegen, The Netherlands
- Department of Radiation Oncology, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Anja Gijtenbeek
- Radboudumc Center of Expertise Neuro-Oncology, 6525 GA Nijmegen, The Netherlands
- Department of Neurology, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Elsmarieke M van de Giessen
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, 1100 DD Amsterdam, The Netherlands
| | - Nelleke Tolboom
- Department of Radiology and Nuclear Medicine, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
| | - Daniela E Oprea-Lager
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, 1100 DD Amsterdam, The Netherlands
| | - Marion Smits
- Department of Radiology & Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, 3015 GD Rotterdam, The Netherlands
- Brain Tumor Center, Erasmus MC Cancer Institute, 3015 GD Rotterdam, The Netherlands
- Medical Delta, 2629 JH Delft, The Netherlands
| | - James Nagarajah
- Department of Medical Imaging, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
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Variability of radiotherapy volume delineation: PSMA PET/MRI and MRI based clinical target volume and lymph node target volume for high-risk prostate cancer. Cancer Imaging 2023; 23:1. [PMID: 36600283 DOI: 10.1186/s40644-022-00518-7] [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: 08/01/2022] [Accepted: 12/25/2022] [Indexed: 01/06/2023] Open
Abstract
PURPOSE A comparative retrospective study to assess the impact of PSMA Ligand PET/MRI ([68 Ga]-Ga-PSMA-11 and [18F]-F-PSMA-1007 PET/MRI) as a new method of target delineation compared to conventional imaging on whole-pelvis radiotherapy for high-risk prostate cancer (PCa). PATIENTS AND METHODS Forty-nine patients with primary high-risk PCa completed the whole-pelvis radiotherapy plan based on PSMA PET/MRI and MRI. The primary endpoint compared the size and overlap of clinical target volume (CTV) and nodal gross tumour volume (GTVn) based on PSMA PET/MRI and MRI. The diagnostic performance of two methods for pelvic lymph node metastasis (PLNM) was evaluated. RESULTS In the radiotherapy planning for high-risk PCa patients, there was a significant correlation between MRI-CTV and PET/MRI-CTV (P = 0.005), as well as between MRI-GTVn and PET/MRI-GTVn (P < 0.001). There are non-significant differences in the CTV and GTVn based on MRI and PET/MRI images (P = 0.660, P = 0.650, respectively). The conformity index (CI), lesion coverage factor (LCF) and Dice similarity coefficient (DSC) of CTVs were 0.999, 0.953 and 0.954. The CI, LCF and DSC of GTVns were 0.927, 0.284, and 0.32. Based on pathological lymph node analysis of 463 lymph nodes from 37 patients, the sensitivity, specificity of PET/MRI in the diagnosis of PLNM were 77.78% and 99.76%, respectively, which were higher than those of MRI (P = 0.011). Eight high-risk PCa patients who finished PSMA PET/MRI changed their N or M stage. CONCLUSION The CTV delineated based on PET/MRI and MRI differ little. The GTVn delineated based on PET/MRI encompasses metastatic pelvic lymph nodes more accurately than MRI and avoids covering pelvic lymph nodes without metastasis. We emphasize the utility of PET/MRI fusion images in GTVn delineation in whole pelvic radiotherapy for PCa. The use of PSMA PET/MRI aids in the realization of more individual and precise radiotherapy for PCa.
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10
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Henssen D, Meijer F, Verburg FA, Smits M. Challenges and opportunities for advanced neuroimaging of glioblastoma. Br J Radiol 2023; 96:20211232. [PMID: 36062962 PMCID: PMC10997013 DOI: 10.1259/bjr.20211232] [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: 11/08/2021] [Revised: 08/10/2022] [Accepted: 08/25/2022] [Indexed: 11/05/2022] Open
Abstract
Glioblastoma is the most aggressive of glial tumours in adults. On conventional magnetic resonance (MR) imaging, these tumours are observed as irregular enhancing lesions with areas of infiltrating tumour and cortical expansion. More advanced imaging techniques including diffusion-weighted MRI, perfusion-weighted MRI, MR spectroscopy and positron emission tomography (PET) imaging have found widespread application to diagnostic challenges in the setting of first diagnosis, treatment planning and follow-up. This review aims to educate readers with regard to the strengths and weaknesses of the clinical application of these imaging techniques. For example, this review shows that the (semi)quantitative analysis of the mentioned advanced imaging tools was found useful for assessing tumour aggressiveness and tumour extent, and aids in the differentiation of tumour progression from treatment-related effects. Although these techniques may aid in the diagnostic work-up and (post-)treatment phase of glioblastoma, so far no unequivocal imaging strategy is available. Furthermore, the use and further development of artificial intelligence (AI)-based tools could greatly enhance neuroradiological practice by automating labour-intensive tasks such as tumour measurements, and by providing additional diagnostic information such as prediction of tumour genotype. Nevertheless, due to the fact that advanced imaging and AI-diagnostics is not part of response assessment criteria, there is no harmonised guidance on their use, while at the same time the lack of standardisation severely hampers the definition of uniform guidelines.
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Affiliation(s)
- Dylan Henssen
- Department of Medical Imaging, Radboud university medical
center, Nijmegen, The Netherlands
| | - Frederick Meijer
- Department of Medical Imaging, Radboud university medical
center, Nijmegen, The Netherlands
| | - Frederik A. Verburg
- Department of Medical Imaging, Radboud university medical
center, Nijmegen, The Netherlands
| | - Marion Smits
- Department of Medical Imaging, Radboud university medical
center, Nijmegen, The Netherlands
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11
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Allard B, Dissaux B, Bourhis D, Dissaux G, Schick U, Salaün PY, Abgral R, Querellou S. Hotspot on 18F-FET PET/CT to Predict Aggressive Tumor Areas for Radiotherapy Dose Escalation Guiding in High-Grade Glioma. Cancers (Basel) 2022; 15:cancers15010098. [PMID: 36612093 PMCID: PMC9817533 DOI: 10.3390/cancers15010098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 12/19/2022] [Accepted: 12/20/2022] [Indexed: 12/28/2022] Open
Abstract
The standard therapy strategy for high-grade glioma (HGG) is based on the maximal surgery followed by radio-chemotherapy (RT-CT) with insufficient control of the disease. Recurrences are mainly localized in the radiation field, suggesting an interest in radiotherapy dose escalation to better control the disease locally. We aimed to identify a similarity between the areas of high uptake on O-(2-[18F]-fluoroethyl)-L-tyrosine (FET) positron emission tomography/computed tomography (PET) before RT-CT, the residual tumor on post-therapy NADIR magnetic resonance imaging (MRI) and the area of recurrence on MRI. This is an ancillary study from the IMAGG prospective trial assessing the interest of FET PET imaging in RT target volume definition of HGG. We included patients with diagnoses of HGG obtained by biopsy or tumor resection. These patients underwent FET PET and brain MRIs, both after diagnosis and before RT-CT. The follow-up consisted of sequential brain MRIs performed every 3 months until recurrence. Tumor delineation on the initial MRI 1 (GTV 1), post-RT-CT NADIR MRI 2 (GTV 2), and progression MRI 3 (GTV 3) were performed semi-automatically and manually adjusted by a neuroradiologist specialist in neuro-oncology. GTV 2 and GTV 3 were then co-registered on FET PET data. Tumor volumes on FET PET (MTV) were delineated using a tumor to background ratio (TBR) ≥ 1.6 and different % SUVmax PET thresholds. Spatial similarity between different volumes was performed using the dice (DICE), Jaccard (JSC), and overlap fraction (OV) indices and compared together in the biopsy or partial surgery group (G1) and the total or subtotal surgery group (G2). Another overlap index (OV') was calculated to determine the threshold with the highest probability of being included in the residual volume after RT-CT on MRI 2 and in MRI 3 (called "hotspot"). A total of 23 patients were included, of whom 22% (n = 5) did not have a NADIR MRI 2 due to a disease progression diagnosed on the first post-RT-CT MRI evaluation. Among the 18 patients who underwent a NADIR MRI 2, the average residual tumor was approximately 71.6% of the GTV 1. A total of 22% of patients (5/23) showed an increase in GTV 2 without diagnosis of true progression by the multidisciplinary team (MDT). Spatial similarity between MTV and GTV 2 and between MTV and GTV 3 were higher using a TBR ≥ 1.6 threshold. These indices were significantly better in the G1 group than the G2 group. In the FET hotspot analysis, the best similarity (good agreement) with GTV 2 was found in the G1 group using a 90% SUVmax delineation method and showed a trend of statistical difference with those (poor agreement) in the G2 group (OV' = 0.67 vs. 0.38, respectively, p = 0.068); whereas the best similarity (good agreement) with GTV 3 was found in the G1 group using a 80% SUVmax delineation method and was significantly higher than those (poor agreement) in the G2 group (OV'= 0.72 vs. 0.35, respectively, p = 0.014). These results showed modest spatial similarity indices between MTV, GTV 2, and GTV 3 of HGG. Nevertheless, the results were significantly improved in patients who underwent only biopsy or partial surgery. TBR ≥ 1.6 and 80-90% SUVmax FET delineation methods showing a good agreement in the hotspot concept for targeting standard dose and radiation boost. These findings need to be tested in a larger randomized prospective study.
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Affiliation(s)
- Bastien Allard
- Nuclear Medicine Department, University Hospital, 29200 Brest, France
- UFR Médecine, University of Western Brittany (UBO), 29200 Brest, France
| | - Brieg Dissaux
- UFR Médecine, University of Western Brittany (UBO), 29200 Brest, France
- GETBO UMR U_1304, Inserm, University of Western Brittany (UBO), 29200 Brest, France
- Radiology Department, University Hospital, 29200 Brest, France
| | - David Bourhis
- Nuclear Medicine Department, University Hospital, 29200 Brest, France
- UFR Médecine, University of Western Brittany (UBO), 29200 Brest, France
- GETBO UMR U_1304, Inserm, University of Western Brittany (UBO), 29200 Brest, France
| | - Gurvan Dissaux
- UFR Médecine, University of Western Brittany (UBO), 29200 Brest, France
- Radiation Oncology Department, University Hospital, 29200 Brest, France
- LaTIM, INSERM 1101, 29200 Brest, France
| | - Ulrike Schick
- UFR Médecine, University of Western Brittany (UBO), 29200 Brest, France
- Radiation Oncology Department, University Hospital, 29200 Brest, France
- LaTIM, INSERM 1101, 29200 Brest, France
| | - Pierre-Yves Salaün
- Nuclear Medicine Department, University Hospital, 29200 Brest, France
- UFR Médecine, University of Western Brittany (UBO), 29200 Brest, France
- GETBO UMR U_1304, Inserm, University of Western Brittany (UBO), 29200 Brest, France
| | - Ronan Abgral
- Nuclear Medicine Department, University Hospital, 29200 Brest, France
- UFR Médecine, University of Western Brittany (UBO), 29200 Brest, France
- GETBO UMR U_1304, Inserm, University of Western Brittany (UBO), 29200 Brest, France
| | - Solène Querellou
- Nuclear Medicine Department, University Hospital, 29200 Brest, France
- UFR Médecine, University of Western Brittany (UBO), 29200 Brest, France
- GETBO UMR U_1304, Inserm, University of Western Brittany (UBO), 29200 Brest, France
- Correspondence:
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Ryan JT, Nakayama M, Gleeson I, Mannion L, Geso M, Kelly J, Ng SP, Hardcastle N. Functional brain imaging interventions for radiation therapy planning in patients with glioblastoma: a systematic review. Radiat Oncol 2022; 17:178. [PMID: 36371225 PMCID: PMC9653002 DOI: 10.1186/s13014-022-02146-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Accepted: 10/14/2022] [Indexed: 11/15/2022] Open
Abstract
RATIONALE This systematic review aims to synthesise the outcomes of different strategies of incorporating functional biological markers in the radiation therapy plans of patients with glioblastoma to support clinicians and further research. METHODS The systematic review protocol was registered on PROSPERO (CRD42021221021). A structured search for publications was performed following PRISMA guidelines. Quality assessment was performed using the Newcastle-Ottawa Scale. Study characteristics, intervention methodology and outcomes were extracted using Covidence. Data analysis focused on radiation therapy target volumes, toxicity, dose distributions, recurrence and survival mapped to functional image-guided radiotherapy interventions. RESULTS There were 5733 citations screened, with 53 citations (n = 32 studies) meeting review criteria. Studies compared standard radiation therapy planning volumes with functional image-derived volumes (n = 20 studies), treated radiation therapy volumes with recurrences (n = 15 studies), the impact on current standard target delineations (n = 9 studies), treated functional volumes and survival (n = 8 studies), functionally guided dose escalation (n = 8 studies), radiomics (n = 4 studies) and optimal organ at risk sparing (n = 3 studies). The approaches to target outlining and dose escalation were heterogeneous. The analysis indicated an improvement in median overall survival of over two months compared with a historical control group. Simultaneous-integrated-boost dose escalation of 72-76 Gy in 30 fractions appeared to have an acceptable toxicity profile when delivered with inverse planning to a volume smaller than 100 cm[Formula: see text]. CONCLUSION There was significant heterogeneity between the approaches taken by different study groups when implementing functional image-guided radiotherapy. It is recommended that functional imaging data be incorporated into the gross tumour volume with appropriate technology-specific margins used to create the clinical target volume when designing radiation therapy plans for patients with glioblastoma.
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Affiliation(s)
- John T Ryan
- Department of Medical Imaging and Radiation Sciences, Monash University, Clayton, Melbourne, Australia
- Medical Radiations Department, School of Health and Biomedical Sciences, STEM College, RMIT University Bundoora, Melbourne, Australia
| | - Masao Nakayama
- Division of Radiation Oncology, Kobe University Graduate School of Medicine, 7-5-2 Kusunokicho, Chuou-ku, Kobe, Japan
| | - Ian Gleeson
- Cancer Research UK RadNet Cambridge, Medical Physics, NHS Foundation Trust, Addenbrookes Hospital, Cambridge, CB2 0QQ UK
| | - Liam Mannion
- Division of Midwifery and Radiography, School of Health Sciences, University of London, Northampton Square, London, UK
| | - Moshi Geso
- Medical Radiations Department, School of Health and Biomedical Sciences, STEM College, RMIT University Bundoora, Melbourne, Australia
| | - Jennifer Kelly
- Medical Radiations Department, School of Health and Biomedical Sciences, STEM College, RMIT University Bundoora, Melbourne, Australia
| | - Sweet Ping Ng
- Department of Radiation Oncology, Olivia Newton-John Cancer Wellness and Research Centre, 145 Studley Rd, Heidelberg, Melbourne, Australia
| | - Nicholas Hardcastle
- Department of Physical Sciences, Peter MacCallum Cancer Centre, 305 Grattan St, Melbourne, Australia
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Radiomic and Volumetric Measurements as Clinical Trial Endpoints—A Comprehensive Review. Cancers (Basel) 2022; 14:cancers14205076. [PMID: 36291865 PMCID: PMC9599928 DOI: 10.3390/cancers14205076] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Revised: 10/12/2022] [Accepted: 10/14/2022] [Indexed: 11/23/2022] Open
Abstract
Simple Summary The extraction of quantitative data from standard-of-care imaging modalities offers opportunities to improve the relevance and salience of imaging biomarkers used in drug development. This review aims to identify the challenges and opportunities for discovering new imaging-based biomarkers based on radiomic and volumetric assessment in the single-site solid tumor sites: breast cancer, rectal cancer, lung cancer and glioblastoma. Developing approaches to harmonize three essential areas: segmentation, validation and data sharing may expedite regulatory approval and adoption of novel cancer imaging biomarkers. Abstract Clinical trials for oncology drug development have long relied on surrogate outcome biomarkers that assess changes in tumor burden to accelerate drug registration (i.e., Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST v1.1) criteria). Drug-induced reduction in tumor size represents an imperfect surrogate marker for drug activity and yet a radiologically determined objective response rate is a widely used endpoint for Phase 2 trials. With the addition of therapies targeting complex biological systems such as immune system and DNA damage repair pathways, incorporation of integrative response and outcome biomarkers may add more predictive value. We performed a review of the relevant literature in four representative tumor types (breast cancer, rectal cancer, lung cancer and glioblastoma) to assess the preparedness of volumetric and radiomics metrics as clinical trial endpoints. We identified three key areas—segmentation, validation and data sharing strategies—where concerted efforts are required to enable progress of volumetric- and radiomics-based clinical trial endpoints for wider clinical implementation.
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14
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Foray C, Barca C, Winkeler A, Wagner S, Hermann S, Schäfers M, Grauer OM, Zinnhardt B, Jacobs AH. Interrogating Glioma-Associated Microglia and Macrophage Dynamics Under CSF-1R Therapy with Multitracer In Vivo PET/MRI. J Nucl Med 2022; 63:1386-1393. [PMID: 35115369 PMCID: PMC9454459 DOI: 10.2967/jnumed.121.263318] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Revised: 01/04/2022] [Indexed: 01/26/2023] Open
Abstract
Glioma-associated microglia and macrophages (GAMMs) are key players in creating an immunosuppressive microenvironment. They can be efficiently targeted by inhibiting the colony-stimulating factor 1 receptor (CSF-1R). We applied noninvasive PET/CT and PET/MRI using 18F-fluoroethyltyrosine (18F-FET) (amino acid metabolism) and N,N-diethyl-2-[4-(2-18F-fluoroethoxy)phenyl]-5,7-dimethylpyrazolo[1,5-a]pyrimidine-3-acetamide (18F-DPA-714) (translocator protein) to understand the role of GAMMs in glioma initiation, monitor in vivo therapy-induced GAMM depletion, and observe GAMM repopulation after drug withdrawal. Methods: C57BL/6 mice (n = 44) orthotopically implanted with syngeneic mouse GL261 glioma cells were treated with different regimens using the CSF-1R inhibitor PLX5622 (6-fluoro-N-((5-fluoro-2-methoxypyridin-3-yl)methyl)-5-((5-methyl-1H-pyrrolo[2,3-b]pyridin-3-yl)methyl)pyridin-2-amine) or vehicle, establishing a preconditioning model and a repopulation model, respectively. The mice underwent longitudinal PET/CT and PET/MRI. Results: The preconditioning model indicated similar tumor growth based on MRI (44.5% ± 24.8%), 18F-FET PET (18.3% ± 11.3%), and 18F-DPA-714 PET (16% ± 19.04%) volume dynamics in all groups, suggesting that GAMMs are not involved in glioma initiation. The repopulation model showed significantly reduced 18F-DPA-714 uptake (-45.6% ± 18.4%), significantly reduced GAMM infiltration even after repopulation, and a significantly decreased tumor volume (-54.29% ± 8.6%) with repopulation as measured by MRI, supported by a significant reduction in 18F-FET uptake (-50.2% ± 5.3%). Conclusion: 18F-FET and 18F-DPA-714 PET/MRI allow noninvasive assessment of glioma growth under various regimens of CSF-1R therapy. CSF-1R-mediated modulation of GAMMs may be of high interest as therapy or cotherapy against glioma.
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Affiliation(s)
- Claudia Foray
- European Institute for Molecular Imaging, University of Münster, Münster, Germany; .,PET Imaging in Drug Design and Development, Münster, Germany
| | - Cristina Barca
- European Institute for Molecular Imaging, University of Münster, Münster, Germany;,PET Imaging in Drug Design and Development, Münster, Germany
| | | | - Stefan Wagner
- Department of Nuclear Medicine, University Hospital Münster, Münster, Germany
| | - Sven Hermann
- European Institute for Molecular Imaging, University of Münster, Münster, Germany
| | - Michael Schäfers
- European Institute for Molecular Imaging, University of Münster, Münster, Germany;,Department of Nuclear Medicine, University Hospital Münster, Münster, Germany
| | - Oliver M. Grauer
- Department of Neurology, University Hospital Münster, Münster, Germany
| | - Bastian Zinnhardt
- European Institute for Molecular Imaging, University of Münster, Münster, Germany;,PET Imaging in Drug Design and Development, Münster, Germany;,Department of Nuclear Medicine, University Hospital Münster, Münster, Germany;,Biomarkers and Translational Technologies, Neurosciences and Rare Diseases, Pharma Research and Early Development, F. Hoffmann-La Roche Ltd., Basel, Switzerland; and
| | - Andreas H. Jacobs
- European Institute for Molecular Imaging, University of Münster, Münster, Germany;,PET Imaging in Drug Design and Development, Münster, Germany;,Department of Geriatrics with Neurology, Johanniter Hospital, and Centre for Integrated Oncology of the University Hospital Bonn, Bonn, Germany
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Diagnostic yield of simultaneous dynamic contrast-enhanced magnetic resonance perfusion measurements and [ 18F]FET PET in patients with suspected recurrent anaplastic astrocytoma and glioblastoma. Eur J Nucl Med Mol Imaging 2022; 49:4677-4691. [PMID: 35907033 PMCID: PMC9605929 DOI: 10.1007/s00259-022-05917-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Accepted: 07/16/2022] [Indexed: 11/04/2022]
Abstract
Purpose Both amino acid positron emission tomography (PET) and magnetic resonance imaging (MRI) blood volume (BV) measurements are used in suspected recurrent high-grade gliomas. We compared the separate and combined diagnostic yield of simultaneously acquired dynamic contrast-enhanced (DCE) perfusion MRI and O-(2-[18F]-fluoroethyl)-L-tyrosine ([18F]FET) PET in patients with anaplastic astrocytoma and glioblastoma following standard therapy. Methods A total of 76 lesions in 60 hybrid [18F]FET PET/MRI scans with DCE MRI from patients with suspected recurrence of anaplastic astrocytoma and glioblastoma were included retrospectively. BV was measured from DCE MRI employing a 2-compartment exchange model (2CXM). Diagnostic performances of maximal tumour-to-background [18F]FET uptake (TBRmax), maximal BV (BVmax) and normalised BVmax (nBVmax) were determined by ROC analysis using 6-month histopathological (n = 28) or clinical/radiographical follow-up (n = 48) as reference. Sensitivity and specificity at optimal cut-offs were determined separately for enhancing and non-enhancing lesions. Results In progressive lesions, all BV and [18F]FET metrics were higher than in non-progressive lesions. ROC analyses showed higher overall ROC AUCs for TBRmax than both BVmax and nBVmax in both lesion-wise (all lesions, p = 0.04) and in patient-wise analysis (p < 0.01). Combining TBRmax with BV metrics did not increase ROC AUC. Lesion-wise positive fraction/sensitivity/specificity at optimal cut-offs were 55%/91%/84% for TBRmax, 45%/77%/84% for BVmax and 59%/84%/72% for nBVmax. Combining TBRmax and best-performing BV cut-offs yielded lesion-wise sensitivity/specificity of 75/97%. The fraction of progressive lesions was 11% in concordant negative lesions, 33% in lesions only BV positive, 64% in lesions only [18F]FET positive and 97% in concordant positive lesions. Conclusion The overall diagnostic accuracy of DCE BV imaging is good, but lower than that of [18F]FET PET. Adding DCE BV imaging did not improve the overall diagnostic accuracy of [18F]FET PET, but may improve specificity and allow better lesion-wise risk stratification than [18F]FET PET alone. Supplementary Information The online version contains supplementary material available at 10.1007/s00259-022-05917-3.
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Withofs N, Kumar R, Alavi A, Hustinx R. Facts and Fictions About [ 18F]FDG versus Other Tracers in Managing Patients with Brain Tumors: It Is Time to Rectify the Ongoing Misconceptions. PET Clin 2022; 17:327-342. [PMID: 35717096 DOI: 10.1016/j.cpet.2022.03.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
MRI is the first-choice imaging technique for brain tumors. Positron emission tomography can be combined together with multiparametric MRI to increase diagnostic confidence. Radiolabeled amino acids have gained wide clinical acceptance. The reported pooled specificity of [18F]FDG positron emission tomography is high and [18F]FDG might still be the first-choice positron emission tomography tracer in cases of World Health Organization grade 3 to 4 gliomas or [18F]FDG-avid tumors, avoiding the use of more expensive and less available radiolabeled amino acids. The present review discusses the additional value of positron emission tomography with a focus on [18F]FDG and radiolabeled amino acids.
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Affiliation(s)
- Nadia Withofs
- Division of Nuclear Medicine and Oncological Imaging, Department of Medical Physics, CHU of Liege, Quartier Hopital, Avenue de l'hopital, 1, Liege 1 4000, Belgium; GIGA-CRC in vivo imaging, University of Liege, GIGA CHU - B34 Quartier Hôpital Avenue de l'Hôpital,11, 4000 Liège, Belgium.
| | - Rakesh Kumar
- Diagnostic Nuclear Medicine Division, All India Institute of Medical Sciences, New Delhi 110029, India
| | - Abass Alavi
- Department of Radiology, Hospital of the University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, USA
| | - Roland Hustinx
- Division of Nuclear Medicine and Oncological Imaging, Department of Medical Physics, CHU of Liege, Quartier Hopital, Avenue de l'hopital, 1, Liege 1 4000, Belgium; GIGA-CRC in vivo imaging, University of Liege, GIGA CHU - B34 Quartier Hôpital Avenue de l'Hôpital,11, 4000 Liège, Belgium
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Ahangari S, Littrup Andersen F, Liv Hansen N, Jakobi Nøttrup T, Berthelsen AK, Folsted Kallehauge J, Richter Vogelius I, Kjaer A, Espe Hansen A, Fischer BM. Multi-parametric PET/MRI for enhanced tumor characterization of patients with cervical cancer. Eur J Hybrid Imaging 2022; 6:7. [PMID: 35378619 PMCID: PMC8980118 DOI: 10.1186/s41824-022-00129-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Accepted: 02/07/2022] [Indexed: 11/10/2022] Open
Abstract
Abstract
Aim
The concept of personalized medicine has brought increased awareness to the importance of inter- and intra-tumor heterogeneity for cancer treatment. The aim of this study was to explore simultaneous multi-parametric PET/MRI prior to chemoradiotherapy for cervical cancer for characterization of tumors and tumor heterogeneity.
Methods
Ten patients with histologically proven primary cervical cancer were examined with multi-parametric 68Ga-NODAGA-E[c(RGDyK)]2-PET/MRI for radiation treatment planning after diagnostic 18F-FDG-PET/CT. Standardized uptake values (SUV) of RGD and FDG, diffusion weighted MRI and the derived apparent diffusion coefficient (ADC), and pharmacokinetic maps obtained from dynamic contrast-enhanced MRI with the Tofts model (iAUC60, Ktrans, ve, and kep) were included in the analysis. The spatial relation between functional imaging parameters in tumors was examined by a correlation analysis and joint histograms at the voxel level. The ability of multi-parametric imaging to identify tumor tissue classes was explored using an unsupervised 3D Gaussian mixture model-based cluster analysis.
Results
Functional MRI and PET of cervical cancers appeared heterogeneous both between patients and spatially within the tumors, and the relations between parameters varied strongly within the patient cohort. The strongest spatial correlation was observed between FDG uptake and ADC (median r = − 0.7). There was moderate voxel-wise correlation between RGD and FDG uptake, and weak correlations between all other modalities. Distinct relations between the ADC and RGD uptake as well as the ADC and FDG uptake were apparent in joint histograms. A cluster analysis using the combination of ADC, FDG and RGD uptake suggested tissue classes which could potentially relate to tumor sub-volumes.
Conclusion
A multi-parametric PET/MRI examination of patients with cervical cancer integrated with treatment planning and including estimation of angiogenesis and glucose metabolism as well as MRI diffusion and perfusion parameters is feasible. A combined analysis of functional imaging parameters indicates a potential of multi-parametric PET/MRI to contribute to a better characterization of tumor heterogeneity than the modalities alone. However, the study is based on small patient numbers and further studies are needed prior to the future design of individually adapted treatment approaches based on multi-parametric functional imaging.
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Henriksen OM, del Mar Álvarez-Torres M, Figueiredo P, Hangel G, Keil VC, Nechifor RE, Riemer F, Schmainda KM, Warnert EAH, Wiegers EC, Booth TC. High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 1: Perfusion and Diffusion Techniques. Front Oncol 2022; 12:810263. [PMID: 35359414 PMCID: PMC8961422 DOI: 10.3389/fonc.2022.810263] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2021] [Accepted: 01/05/2022] [Indexed: 01/16/2023] Open
Abstract
Objective Summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and highlight the latest bench-to-bedside developments. Methods Experts in advanced MRI techniques applied to high-grade glioma treatment response assessment convened through a European framework. Current evidence regarding the potential for monitoring biomarkers in adult high-grade glioma is reviewed, and individual modalities of perfusion, permeability, and microstructure imaging are discussed (in Part 1 of two). In Part 2, we discuss modalities related to metabolism and/or chemical composition, appraise the clinic readiness of the individual modalities, and consider post-processing methodologies involving the combination of MRI approaches (multiparametric imaging) or machine learning (radiomics). Results High-grade glioma vasculature exhibits increased perfusion, blood volume, and permeability compared with normal brain tissue. Measures of cerebral blood volume derived from dynamic susceptibility contrast-enhanced MRI have consistently provided information about brain tumor growth and response to treatment; it is the most clinically validated advanced technique. Clinical studies have proven the potential of dynamic contrast-enhanced MRI for distinguishing post-treatment related effects from recurrence, but the optimal acquisition protocol, mode of analysis, parameter of highest diagnostic value, and optimal cut-off points remain to be established. Arterial spin labeling techniques do not require the injection of a contrast agent, and repeated measurements of cerebral blood flow can be performed. The absence of potential gadolinium deposition effects allows widespread use in pediatric patients and those with impaired renal function. More data are necessary to establish clinical validity as monitoring biomarkers. Diffusion-weighted imaging, apparent diffusion coefficient analysis, diffusion tensor or kurtosis imaging, intravoxel incoherent motion, and other microstructural modeling approaches also allow treatment response assessment; more robust data are required to validate these alone or when applied to post-processing methodologies. Conclusion Considerable progress has been made in the development of these monitoring biomarkers. Many techniques are in their infancy, whereas others have generated a larger body of evidence for clinical application.
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Affiliation(s)
- Otto M. Henriksen
- Department of Clinical Physiology, Nuclear Medicine and PET, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
| | | | - Patricia Figueiredo
- Department of Bioengineering and Institute for Systems and Robotics-Lisboa, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Gilbert Hangel
- Department of Neurosurgery, Medical University, Vienna, Austria
- High-Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University, Vienna, Austria
| | - Vera C. Keil
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, Netherlands
| | - Ruben E. Nechifor
- International Institute for the Advanced Studies of Psychotherapy and Applied Mental Health, Department of Clinical Psychology and Psychotherapy, Babes-Bolyai University, Cluj-Napoca, Romania
| | - Frank Riemer
- Mohn Medical Imaging and Visualization Centre (MMIV), Department of Radiology, Haukeland University Hospital, Bergen, Norway
| | - Kathleen M. Schmainda
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, WI, United States
| | | | - Evita C. Wiegers
- Department of Radiology, University Medical Center Utrecht, Utrecht, Netherlands
| | - Thomas C. Booth
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School of Biomedical Engineering and Imaging Sciences, St. Thomas’ Hospital, King’s College London, London, United Kingdom
- Department of Neuroradiology, King’s College Hospital NHS Foundation Trust, London, United Kingdom
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Booth TC, Wiegers EC, Warnert EAH, Schmainda KM, Riemer F, Nechifor RE, Keil VC, Hangel G, Figueiredo P, Álvarez-Torres MDM, Henriksen OM. High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 2: Spectroscopy, Chemical Exchange Saturation, Multiparametric Imaging, and Radiomics. Front Oncol 2022; 11:811425. [PMID: 35340697 PMCID: PMC8948428 DOI: 10.3389/fonc.2021.811425] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 12/28/2021] [Indexed: 01/16/2023] Open
Abstract
Objective To summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and to highlight the latest bench-to-bedside developments. Methods The current evidence regarding the potential for monitoring biomarkers was reviewed and individual modalities of metabolism and/or chemical composition imaging discussed. Perfusion, permeability, and microstructure imaging were similarly analyzed in Part 1 of this two-part review article and are valuable reading as background to this article. We appraise the clinic readiness of all the individual modalities and consider methodologies involving machine learning (radiomics) and the combination of MRI approaches (multiparametric imaging). Results The biochemical composition of high-grade gliomas is markedly different from healthy brain tissue. Magnetic resonance spectroscopy allows the simultaneous acquisition of an array of metabolic alterations, with choline-based ratios appearing to be consistently discriminatory in treatment response assessment, although challenges remain despite this being a mature technique. Promising directions relate to ultra-high field strengths, 2-hydroxyglutarate analysis, and the use of non-proton nuclei. Labile protons on endogenous proteins can be selectively targeted with chemical exchange saturation transfer to give high resolution images. The body of evidence for clinical application of amide proton transfer imaging has been building for a decade, but more evidence is required to confirm chemical exchange saturation transfer use as a monitoring biomarker. Multiparametric methodologies, including the incorporation of nuclear medicine techniques, combine probes measuring different tumor properties. Although potentially synergistic, the limitations of each individual modality also can be compounded, particularly in the absence of standardization. Machine learning requires large datasets with high-quality annotation; there is currently low-level evidence for monitoring biomarker clinical application. Conclusion Advanced MRI techniques show huge promise in treatment response assessment. The clinical readiness analysis highlights that most monitoring biomarkers require standardized international consensus guidelines, with more facilitation regarding technique implementation and reporting in the clinic.
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Affiliation(s)
- Thomas C. Booth
- School of Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas’ Hospital, London, United Kingdom
- Department of Neuroradiology, King’s College Hospital NHS Foundation Trust, London, United Kingdom
| | - Evita C. Wiegers
- Department of Radiology, University Medical Center Utrecht, Utrecht, Netherlands
| | | | - Kathleen M. Schmainda
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Frank Riemer
- Mohn Medical Imaging and Visualization Centre (MMIV), Department of Radiology, Haukeland University Hospital, Bergen, Norway
| | - Ruben E. Nechifor
- Department of Clinical Psychology and Psychotherapy International Institute for the Advanced Studies of Psychotherapy and Applied Mental Health, Babes-Bolyai University, Cluj-Napoca, Romania
| | - Vera C. Keil
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, location VUmc, Amsterdam, Netherlands
| | - Gilbert Hangel
- Department of Neurosurgery & High-Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria
| | - Patrícia Figueiredo
- Department of Bioengineering and Institute for Systems and Robotics - Lisboa, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | | | - Otto M. Henriksen
- Department of Clinical Physiology, Nuclear medicine and PET, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
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Brighi C, Puttick S, Li S, Keall P, Neville K, Waddington D, Bourgeat P, Gillman A, Fay M. A novel semiautomated method for background activity and biological tumour volume definition to improve standardisation of 18F-FET PET imaging in glioblastoma. EJNMMI Phys 2022; 9:9. [PMID: 35122529 PMCID: PMC8818070 DOI: 10.1186/s40658-022-00438-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 01/24/2022] [Indexed: 11/10/2022] Open
Abstract
Background Multicentre clinical trials evaluating the role of 18F-Fluoroethyl-l-tyrosine (18F-FET) PET as a diagnostic biomarker in glioma management have highlighted a need for standardised methods of data analysis. 18F-FET uptake normalised against background in the contralateral brain is a standard imaging technique to delineate the biological tumour volume (BTV). Quantitative analysis of 18F-FET PET images requires a consistent and robust background activity. Currently, defining background activity involves the manual selection of an arbitrary region of interest, a process that is subject to large variability. This study aims to eliminate methodological errors in background activity definition through the introduction of a semiautomated method for region of interest selection. A new method for background activity definition, involving the semiautomated generation of mirror-image (MI) reference regions, was compared with the current state-of-the-art method, involving manually drawing crescent-shape (gCS) reference regions. The MI and gCS methods were tested by measuring values of background activity and resulting BTV of 18F-FET PET scans of ten patients with recurrent glioblastoma multiforme generated from inputs provided by seven readers. To assess intra-reader variability, each scan was evaluated six times by each reader. Intra- and inter-reader variability in background activity and BTV definition was assessed by means of coefficient of variation. Results Compared to the gCS method, the MI method showed significantly lower intra- and inter-reader variability both in background activity and in BTV definition. Conclusions The proposed semiautomated MI method minimises intra- and inter-reader variability, providing a valuable approach for standardisation of 18F-FET PET quantitative parameters. Trial registration ANZCTR, ACTRN12618001346268. Registered 9 August 2018, https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=374253 Supplementary Information The online version contains supplementary material available at 10.1186/s40658-022-00438-2.
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Affiliation(s)
- Caterina Brighi
- ACRF Image X Institute, Sydney School of Health Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia.
| | - Simon Puttick
- Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organization, Royal Brisbane and Women's Hospital, Brisbane, Australia
| | - Shenpeng Li
- Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organization, Royal Brisbane and Women's Hospital, Brisbane, Australia
| | - Paul Keall
- ACRF Image X Institute, Sydney School of Health Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia
| | | | - David Waddington
- ACRF Image X Institute, Sydney School of Health Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia
| | - Pierrick Bourgeat
- Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organization, Royal Brisbane and Women's Hospital, Brisbane, Australia
| | - Ashley Gillman
- Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organization, Royal Brisbane and Women's Hospital, Brisbane, Australia
| | - Michael Fay
- GenesisCare, Newcastle, Australia.,School of Medicine and Public Health, The University of Newcastle, Newcastle, Australia
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Booth TC, Grzeda M, Chelliah A, Roman A, Al Busaidi A, Dragos C, Shuaib H, Luis A, Mirchandani A, Alparslan B, Mansoor N, Lavrador J, Vergani F, Ashkan K, Modat M, Ourselin S. Imaging Biomarkers of Glioblastoma Treatment Response: A Systematic Review and Meta-Analysis of Recent Machine Learning Studies. Front Oncol 2022; 12:799662. [PMID: 35174084 PMCID: PMC8842649 DOI: 10.3389/fonc.2022.799662] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Accepted: 01/03/2022] [Indexed: 12/21/2022] Open
Abstract
OBJECTIVE Monitoring biomarkers using machine learning (ML) may determine glioblastoma treatment response. We systematically reviewed quality and performance accuracy of recently published studies. METHODS Following Preferred Reporting Items for Systematic Reviews and Meta-Analysis: Diagnostic Test Accuracy, we extracted articles from MEDLINE, EMBASE and Cochrane Register between 09/2018-01/2021. Included study participants were adults with glioblastoma having undergone standard treatment (maximal resection, radiotherapy with concomitant and adjuvant temozolomide), and follow-up imaging to determine treatment response status (specifically, distinguishing progression/recurrence from progression/recurrence mimics, the target condition). Using Quality Assessment of Diagnostic Accuracy Studies Two/Checklist for Artificial Intelligence in Medical Imaging, we assessed bias risk and applicability concerns. We determined test set performance accuracy (sensitivity, specificity, precision, F1-score, balanced accuracy). We used a bivariate random-effect model to determine pooled sensitivity, specificity, area-under the receiver operator characteristic curve (ROC-AUC). Pooled measures of balanced accuracy, positive/negative likelihood ratios (PLR/NLR) and diagnostic odds ratio (DOR) were calculated. PROSPERO registered (CRD42021261965). RESULTS Eighteen studies were included (1335/384 patients for training/testing respectively). Small patient numbers, high bias risk, applicability concerns (particularly confounding in reference standard and patient selection) and low level of evidence, allow limited conclusions from studies. Ten studies (10/18, 56%) included in meta-analysis gave 0.769 (0.649-0.858) sensitivity [pooled (95% CI)]; 0.648 (0.749-0.532) specificity; 0.706 (0.623-0.779) balanced accuracy; 2.220 (1.560-3.140) PLR; 0.366 (0.213-0.572) NLR; 6.670 (2.800-13.500) DOR; 0.765 ROC-AUC. CONCLUSION ML models using MRI features to distinguish between progression and mimics appear to demonstrate good diagnostic performance. However, study quality and design require improvement.
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Affiliation(s)
- Thomas C. Booth
- School of Biomedical Engineering & Imaging Sciences, King’s College London, St. Thomas’ Hospital, London, United Kingdom
- Department of Neuroradiology, King’s College Hospital National Health Service Foundation Trust, London, United Kingdom
| | - Mariusz Grzeda
- School of Biomedical Engineering & Imaging Sciences, King’s College London, St. Thomas’ Hospital, London, United Kingdom
| | - Alysha Chelliah
- School of Biomedical Engineering & Imaging Sciences, King’s College London, St. Thomas’ Hospital, London, United Kingdom
| | - Andrei Roman
- Department of Radiology, Guy’s & St. Thomas’ National Health Service Foundation Trust, London, United Kingdom
- Department of Radiology, The Oncology Institute “Prof. Dr. Ion Chiricuţă” Cluj-Napoca, Cluj-Napoca, Romania
| | - Ayisha Al Busaidi
- Department of Neuroradiology, King’s College Hospital National Health Service Foundation Trust, London, United Kingdom
| | - Carmen Dragos
- Department of Radiology, Buckinghamshire Healthcare National Health Service Trust, Amersham, United Kingdom
| | - Haris Shuaib
- Department of Medical Physics, Guy’s & St. Thomas’ National Health Service Foundation Trust, London, United Kingdom
- Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Aysha Luis
- Department of Neuroradiology, King’s College Hospital National Health Service Foundation Trust, London, United Kingdom
| | - Ayesha Mirchandani
- Department of Radiology, Cambridge University Hospitals National Health Service Foundation Trust, Cambridge, United Kingdom
| | - Burcu Alparslan
- Department of Neuroradiology, King’s College Hospital National Health Service Foundation Trust, London, United Kingdom
- Department of Radiology, Kocaeli University, İzmit, Turkey
| | - Nina Mansoor
- Department of Neuroradiology, King’s College Hospital National Health Service Foundation Trust, London, United Kingdom
| | - Jose Lavrador
- Department of Neurosurgery, King’s College Hospital National Health Service Foundation Trust, London, United Kingdom
| | - Francesco Vergani
- Department of Neurosurgery, King’s College Hospital National Health Service Foundation Trust, London, United Kingdom
| | - Keyoumars Ashkan
- Department of Neurosurgery, King’s College Hospital National Health Service Foundation Trust, London, United Kingdom
| | - Marc Modat
- School of Biomedical Engineering & Imaging Sciences, King’s College London, St. Thomas’ Hospital, London, United Kingdom
| | - Sebastien Ourselin
- School of Biomedical Engineering & Imaging Sciences, King’s College London, St. Thomas’ Hospital, London, United Kingdom
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Li S, Zhang B, Zhang P, Xue C, Deng J, Liu X, Zhou J. Postoperative progression of intracranial grade II-III solitary fibrous tumor/hemangiopericytoma: predictive value of preoperative magnetic resonance imaging semantic features. Acta Radiol 2021; 64:301-310. [PMID: 34923852 DOI: 10.1177/02841851211066757] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Preoperative prediction of postoperative tumor progression of intracranial grade II-III hemangiopericytoma is the basis for clinical treatment decisions. PURPOSE To use preoperative magnetic resonance imaging (MRI) semantic features for predicting postoperative tumor progression in patients with intracranial grade II-III solitary fibrous tumor/hemangiopericytoma (SFT/HPC). MATERIAL AND METHODS We retrospectively analyzed the preoperative MRI data of 42 patients with intracranial grade II-III SFT/HPC, as confirmed by surgical resection and pathology in our hospital from October 2010 to October 2017, who were followed up for evaluation of recurrence, metastasis, or death. We applied strict inclusion and exclusion criteria and finally included 37 patients. The follow-up time was in the range of 8-120 months (mean = 57.1 months). RESULTS Single-factor survival analysis revealed that tumor grade (log-rank, P = 0.024), broad-based tumor attachment to the dura mater (log-rank, P = 0.009), a blurred tumor-brain interface (log-rank, P = 0.008), skull invasion (log-rank, P = 0.002), and the absence of postoperative radiotherapy (log-rank, P = 0.006) predicted postoperative intracranial SFT/HPC progression. Multivariate survival analysis revealed that tumor grade (P = 0.009; hazard ratio [HR] = 11.42; 95% confidence interval [CI] = 1.832-71.150), skull invasion (P = 0.014; HR = 5.72; 95% CI = 1.421-22.984), and the absence of postoperative radiotherapy (P = 0.001; HR = 0.05; 95% CI = 0.008-0.315) were independent predictors of postoperative intracranial SFT/HPC progression. CONCLUSION Broad-based tumor attachment to the dura mater, skull invasion, and blurring of the tumor-brain interface can predict postoperative intracranial SFT/HPC progression.
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Affiliation(s)
- Shenglin Li
- Department of Radiology, Lanzhou University Second Hospital, Lanzhou, PR China
- Second Clinical School, Lanzhou University, Lanzhou, PR China
- Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, PR China
- Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, PR China
| | - Bin Zhang
- Department of Radiology, Lanzhou University Second Hospital, Lanzhou, PR China
- Second Clinical School, Lanzhou University, Lanzhou, PR China
- Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, PR China
- Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, PR China
| | - Peng Zhang
- Department of Pathology, Second Hospital of Lanzhou University, Lanzhou, PR China
| | - Caiqiang Xue
- Department of Radiology, Lanzhou University Second Hospital, Lanzhou, PR China
- Second Clinical School, Lanzhou University, Lanzhou, PR China
- Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, PR China
- Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, PR China
| | - Juan Deng
- Department of Radiology, Lanzhou University Second Hospital, Lanzhou, PR China
- Second Clinical School, Lanzhou University, Lanzhou, PR China
- Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, PR China
- Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, PR China
| | - Xianwang Liu
- Department of Radiology, Lanzhou University Second Hospital, Lanzhou, PR China
- Second Clinical School, Lanzhou University, Lanzhou, PR China
- Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, PR China
- Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, PR China
| | - Junlin Zhou
- Department of Radiology, Lanzhou University Second Hospital, Lanzhou, PR China
- Second Clinical School, Lanzhou University, Lanzhou, PR China
- Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, PR China
- Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, PR China
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Wang J, Yi X, Fu Y, Pang P, Deng H, Tang H, Han Z, Li H, Nie J, Gong G, Hu Z, Tan Z, Chen BT. Preoperative Magnetic Resonance Imaging Radiomics for Predicting Early Recurrence of Glioblastoma. Front Oncol 2021; 11:769188. [PMID: 34778086 PMCID: PMC8579096 DOI: 10.3389/fonc.2021.769188] [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: 09/01/2021] [Accepted: 10/11/2021] [Indexed: 01/03/2023] Open
Abstract
Purpose Early recurrence of glioblastoma after standard treatment makes patient care challenging. This study aimed to assess preoperative magnetic resonance imaging (MRI) radiomics for predicting early recurrence of glioblastoma. Patients and Methods A total of 122 patients (training cohort: n = 86; validation cohort: n = 36) with pathologically confirmed glioblastoma were included in this retrospective study. Preoperative brain MRI images were analyzed for both radiomics and the Visually Accessible Rembrandt Image (VASARI) features of glioblastoma. Models incorporating MRI radiomics, the VASARI parameters, and clinical variables were developed and presented in a nomogram. Performance was assessed based on calibration, discrimination, and clinical usefulness. Results The nomogram consisting of the radiomic signatures, the VASARI parameters, and blood urea nitrogen (BUN) values showed good discrimination between the patients with early recurrence and those with later recurrence, with an area under the curve of 0.85 (95% CI, 0.77-0.94) in the training cohort and 0.84 [95% CI, 0.71-0.97] in the validation cohort. Decision curve analysis demonstrated favorable clinical application of the nomogram. Conclusion This study showed the potential usefulness of preoperative brain MRI radiomics in predicting the early recurrence of glioblastoma, which should be helpful in personalized management of glioblastoma.
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Affiliation(s)
- Jing Wang
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, China
| | - Xiaoping Yi
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Geriatric Disorders, Changsha, China.,Hunan Engineering Research Center of Skin Health and Disease, Changsha, China.,Hunan Key Laboratory of Skin Cancer and Psoriasis, Changsha, China
| | - Yan Fu
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Geriatric Disorders (Xiangya Hospital), Central South University, Changsha, China
| | - Peipei Pang
- Department of Pharmaceuticals Diagnosis, GE Healthcare, Hangzhou, China
| | - Huihuang Deng
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, China
| | - Haiyun Tang
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, China
| | - Zaide Han
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, China
| | - Haiping Li
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, China
| | - Jilin Nie
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, China
| | - Guanghui Gong
- Department of Pathology, Xiangya Hospital, Central South University, Changsha, China
| | - Zhongliang Hu
- Department of Pathology, Xiangya Hospital, Central South University, Changsha, China
| | - Zeming Tan
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China
| | - Bihong T Chen
- Department of Diagnostic Radiology, City of Hope National Medical Center, Duarte, CA, United States
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Cook TA, Jayamanne DT, Wheeler HR, Wong MHF, Parkinson JF, Cook RJ, Kastelan MA, Cove NJ, Brown C, Back MF. Redo craniotomy or bevacizumab for symptomatic steroid-refractory true or pseudoprogression following IMRT for glioblastoma. Neurooncol Pract 2021; 8:601-608. [PMID: 34594572 DOI: 10.1093/nop/npab034] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Background There is minimal evidence to support decision making for symptomatic steroid-refractory pseudoprogression or true progression occurring after intensity-modulated radiation therapy (IMRT) for glioblastoma (GBM). This study audited the survival outcome of patients managed with redo craniotomy (RedoSx) or bevacizumab (BEV) for steroid-refractory mass effect after IMRT for GBM. Methods Patients with GBM managed between 2008 and 2019 with the EORTC-NCIC Protocol were entered into a prospective database. Patients with symptomatic steroid-refractory mass effect within 6 months of IMRT managed with either RedoSx or BEV were identified for analysis. For the primary endpoint of median overall survival (OS) postintervention, outcome was analyzed in regards to potential prognostic factors, and differences between groups were assessed by log-rank analyses. Results Of the 399 patients managed with the EORTC-NCIC Protocol, 78 required an intervention within 6 months of IMRT completion for either true or pseudoprogression (49 with RedoSx and 29 with BEV). Subsequently, 20 of the 43 patients managed with RedoSx when BEV was clinically available, required salvage with BEV within 6 months after RedoSx. Median OS postintervention was 8.7 months (95% CI: 7.84-11.61) for the total group; and 8.7 months (95% CI: 6.8-13.1) for RedoSx and 9.4 months (95% CI: 7.8-13.6) for BEV (P = .38). Subsequent use of BEV in RedoSx patients was not associated with improved survival compared with RedoSx alone (P = .10). Age, time from IMRT, and ECOG performance status were not associated with OS. In the RedoSx patients, immunohistochemical features such as Ki-67% reduction correlated with survival. The presence of pure necrosis and residual tumor cells only had improved survival compared with the presence of gross tumor (P < .001). Conclusions At time of symptomatic steroid-refractory true or pseudoprogression following IMRT for GBM, BEV was equivalent to RedoSx in terms of OS. Pseudoprogression with residual cells at RedoSx was not associated with worse outcome compared to pure necrosis.
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Affiliation(s)
- Theresa A Cook
- Central Coast Cancer Centre, Gosford Hospital, Gosford, New South Wales, Australia
| | - Dasantha T Jayamanne
- Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, New South Wales, Australia
| | - Helen R Wheeler
- Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, New South Wales, Australia.,Sydney Medical School, University of Sydney, Sydney, New South Wales, Australia
| | - Matthew H F Wong
- Central Coast Cancer Centre, Gosford Hospital, Gosford, New South Wales, Australia
| | - Jonathon F Parkinson
- Sydney Medical School, University of Sydney, Sydney, New South Wales, Australia.,The Brain Cancer Group, Sydney, New South Wales, Australia.,Department of Neurosurgery, Royal North Shore Hospital, Sydney, New South Wales, Australia
| | - Raymond J Cook
- Department of Neurosurgery, Royal North Shore Hospital, Sydney, New South Wales, Australia
| | - Marina A Kastelan
- Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, New South Wales, Australia.,The Brain Cancer Group, Sydney, New South Wales, Australia
| | - Nicola J Cove
- Central Coast Cancer Centre, Gosford Hospital, Gosford, New South Wales, Australia
| | - Christopher Brown
- Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, New South Wales, Australia
| | - Michael F Back
- Central Coast Cancer Centre, Gosford Hospital, Gosford, New South Wales, Australia.,Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, New South Wales, Australia.,Genesis Cancer Care, Sydney, New South Wales, Australia.,Sydney Medical School, University of Sydney, Sydney, New South Wales, Australia.,The Brain Cancer Group, Sydney, New South Wales, Australia
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25
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Laudicella R, Bauckneht M, Cuppari L, Donegani MI, Arnone A, Baldari S, Burger IA, Quartuccio N. Emerging applications of imaging in glioma: focus on PET/MRI and radiomics. Clin Transl Imaging 2021. [DOI: 10.1007/s40336-021-00464-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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26
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Ferjančič P, Ebert MA, Francis R, Nowak AK, Jeraj R. Repeatability of Quantitative 18F-FET PET in Glioblastoma. Biomed Phys Eng Express 2021; 7. [PMID: 33887712 DOI: 10.1088/2057-1976/abfae9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2020] [Accepted: 04/22/2021] [Indexed: 12/16/2022]
Abstract
Purpose: O-(2-[18F]fluoroethyl)-L-tyrosine (FET), a PET radiotracer of amino acid uptake, has shown potential for diagnosis and treatment planning in patients with glioblastoma (GBM). To improve quantitative assessment of FET PET imaging, we evaluated the repeatability of uptake of this tracer in patients with GBM.Methods: Test-retest FET PET imaging was performed on 8 patients with histologically confirmed GBM, who previously underwent surgical resection of the tumour. Data were acquired according to the protocol of a prospective clinical trial validating FET PET as a clinical tool in GBM. SUVmean, SUVmaxand SUV98%metrics were extracted for both test and retest images and used to calculate 95% Bland-Altman limits of agreement (LoA) on lesion-level, as well as on volumes of varying sizes. Impact of healthy brain normalization on repeatability of lesion SUV metrics was evaluated.Results: Tumour LoA were [0.72, 1.46] for SUVmeanand SUVtotal, [0.79,1.23] for SUVmax, and [0.80,1.18] for SUV98%. Healthy brain LoA were [0.80,1.25] for SUVmean, [0.80,1.25] for SUVmax, and [0.81,1.23] for SUV98%. Voxel-level SUV LoA were [0.76, 1.32] for tumour volumes and [0.80, 1.25] for healthy brain. When sampled over maximum volume, SUV LoA were [0.90,1.12] for tumour and [0.92,1.08] for healthy brain. Normalization of uptake using healthy brain volumes was found to improve repeatability, but not after normalization volume size of about 15 cm3.Conclusions Advances in Knowledge and Implications for Patient Care: Repeatability of FET PET is comparable to existing tracers such as FDG and FLT. Healthy brain uptake is slightly more repeatable than uptake of tumour volumes. Repeatability was found to increase with sampled volume. SUV normalization between scans using healthy brain uptake should be performed using volumes at least 15 cm3in size to ensure best imaging repeatability.
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Affiliation(s)
- Peter Ferjančič
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, United States of America
| | - Martin A Ebert
- Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia.,Medical School, University of Western Australia, Crawley, Western Australia, Australia.,5D Clinics, Perth, Western Australia, Australia
| | - Roslyn Francis
- Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia.,Medical School, University of Western Australia, Crawley, Western Australia, Australia
| | - Anna K Nowak
- Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia.,Medical School, University of Western Australia, Crawley, Western Australia, Australia
| | - Robert Jeraj
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, United States of America.,Faculty of Mathematics and Physics, University of Ljubljana, Ljubljana, Slovenia
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d’Este SH, Nielsen MB, Hansen AE. Visualizing Glioma Infiltration by the Combination of Multimodality Imaging and Artificial Intelligence, a Systematic Review of the Literature. Diagnostics (Basel) 2021; 11:diagnostics11040592. [PMID: 33806195 PMCID: PMC8067218 DOI: 10.3390/diagnostics11040592] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Accepted: 03/23/2021] [Indexed: 01/14/2023] Open
Abstract
The aim of this study was to systematically review the literature concerning the integration of multimodality imaging with artificial intelligence methods for visualization of tumor cell infiltration in glioma patients. The review was performed in accordance with the preferred reporting items for systematic reviews and meta-analysis (PRISMA) guidelines. The literature search was conducted in PubMed, Embase, The Cochrane Library and Web of Science and yielded 1304 results. 14 studies were included in the qualitative analysis. The reference standard for tumor infiltration was either histopathology or recurrence on image follow-up. Critical assessment was performed according to the Quality Assessment of Diagnostic Accuracy Studies (QUADAS2). All studies concluded their findings to be of significant value for future clinical practice. Diagnostic test accuracy reached an area under the curve of 0.74–0.91 reported in six studies. There was no consensus with regard to included image modalities, models or training and test strategies. The integration of artificial intelligence with multiparametric imaging shows promise for visualizing tumor cell infiltration in glioma patients. This approach can possibly optimize surgical resection margins and help provide personalized radiotherapy planning.
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Affiliation(s)
- Sabrina Honoré d’Este
- Department of Diagnostic Radiology, Copenhagen University Hospital—Rigshospitalet, 2100 Copenhagen, Denmark; (M.B.N.); (A.E.H.)
- Correspondence:
| | - Michael Bachmann Nielsen
- Department of Diagnostic Radiology, Copenhagen University Hospital—Rigshospitalet, 2100 Copenhagen, Denmark; (M.B.N.); (A.E.H.)
- Department of Clinical Medicine, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Adam Espe Hansen
- Department of Diagnostic Radiology, Copenhagen University Hospital—Rigshospitalet, 2100 Copenhagen, Denmark; (M.B.N.); (A.E.H.)
- Department of Clinical Medicine, University of Copenhagen, 2200 Copenhagen, Denmark
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28
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Seidlitz A, Beuthien-Baumann B, Löck S, Jentsch C, Platzek I, Zöphel K, Linge A, Kotzerke J, Petr J, van den Hoff J, Steinbach J, Krex D, Schmitz-Schackert G, Falk M, Baumann M, Krause M. Final Results of the Prospective Biomarker Trial PETra: [ 11C]-MET-Accumulation in Postoperative PET/MRI Predicts Outcome after Radiochemotherapy in Glioblastoma. Clin Cancer Res 2021; 27:1351-1360. [PMID: 33376095 DOI: 10.1158/1078-0432.ccr-20-1775] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Revised: 07/24/2020] [Accepted: 12/22/2020] [Indexed: 11/16/2022]
Abstract
PURPOSE This prospective trial investigates the association of time to recurrence (TTR) in glioblastoma with [11C]methionine (MET) tracer uptake before postoperative radiochemotherapy (RCT) aiming to guide radiotherapy boost regions. EXPERIMENTAL DESIGN Between 2013 and 2016, 102 patients with glioblastoma were recruited. RCT was performed with concurrent and adjuvant temozolomide to a total dose of 60 Gy. Tumor residues in postresection PET and MRI were together defined as gross tumor volumes for radiotherapy treatment planning. [11C]methionine (MET)-PET/MRI was performed before RCT and at each follow-up. RESULTS The primary hypothesis of a longer TTR for patients without increased tracer accumulation in postoperative MET-PET was confirmed in 89 patients. With 18.9 months (95% confidence interval, 9.3-28.5 months), median TTR was significantly (P < 0.001) longer for patients without (n = 29, 32.6%) as compared with 6.3 months (3.6-8.9) for patients with MET accumulation (n = 60, 67.4%) in pre-RCT PET. Although MRI often did not detect all PET-positive regions, an unfavorable impact of residual tumor in postsurgical MRI (n = 38, 42.7%) on TTR was observed [4.6 (4.2-5.1) vs. 15.5 months (6.0-24.9), P < 0.001]. Significant multivariable predictors for TTR were MRI positivity, PET-positive volume, and O6-methylguanine DNA methyltransferase (MGMT) hypermethylation. CONCLUSIONS Postsurgical amino acid PET has prognostic value for TTR after RCT in glioblastoma. Because of the added value of the metabolic beyond the pure structural information, it should complement MRI in radiotherapy planning if available with reasonable effort, at least in the context of maximal therapy. Furthermore, the spatial correlation of regions of recurrence with PET-positive volumes could provide a bioimaging basis for further trials, for example, testing local radiation dose escalation.
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Affiliation(s)
- Annekatrin Seidlitz
- Department of Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany. .,National Center for Tumor Diseases (NCT), Partner Site Dresden, Germany: German Cancer Research Center (DKFZ), Heidelberg, Germany; Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany, and Helmholtz Association/Helmholtz-Zentrum Dresden - Rossendorf (HZDR), Dresden, Germany.,OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany.,German Cancer Research Center (DKFZ), Heidelberg and German Cancer Consortium (DKTK) partner site, Dresden, Germany
| | - Bettina Beuthien-Baumann
- Department of Nuclear Medicine, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.,German Cancer Research Center (DKFZ), Department of Radiology, Heidelberg, Germany
| | - Steffen Löck
- Department of Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.,OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany.,German Cancer Research Center (DKFZ), Heidelberg and German Cancer Consortium (DKTK) partner site, Dresden, Germany
| | - Christina Jentsch
- Department of Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.,National Center for Tumor Diseases (NCT), Partner Site Dresden, Germany: German Cancer Research Center (DKFZ), Heidelberg, Germany; Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany, and Helmholtz Association/Helmholtz-Zentrum Dresden - Rossendorf (HZDR), Dresden, Germany.,OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany
| | - Ivan Platzek
- Institute of Radiology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Klaus Zöphel
- Department of Nuclear Medicine, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Annett Linge
- Department of Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.,National Center for Tumor Diseases (NCT), Partner Site Dresden, Germany: German Cancer Research Center (DKFZ), Heidelberg, Germany; Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany, and Helmholtz Association/Helmholtz-Zentrum Dresden - Rossendorf (HZDR), Dresden, Germany.,OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany.,German Cancer Research Center (DKFZ), Heidelberg and German Cancer Consortium (DKTK) partner site, Dresden, Germany
| | - Jörg Kotzerke
- Department of Nuclear Medicine, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Jan Petr
- Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany.,Department of Biomedical Engineering, Rochester Institute of Technology, Rochester, New York
| | - Jörg van den Hoff
- Department of Nuclear Medicine, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.,Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany
| | - Jörg Steinbach
- Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany.,Department of Chemistry and Food Chemistry, TU Dresden, Dresden, Germany
| | - Dietmar Krex
- Department of Neurosurgery, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Gabriele Schmitz-Schackert
- Department of Neurosurgery, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Monique Falk
- Department of Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.,National Center for Tumor Diseases (NCT), Partner Site Dresden, Germany: German Cancer Research Center (DKFZ), Heidelberg, Germany; Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany, and Helmholtz Association/Helmholtz-Zentrum Dresden - Rossendorf (HZDR), Dresden, Germany.,German Cancer Research Center (DKFZ), Heidelberg and German Cancer Consortium (DKTK) partner site, Dresden, Germany
| | - Michael Baumann
- Department of Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.,OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany.,Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiooncology, Dresden, Germany.,German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Mechthild Krause
- Department of Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.,National Center for Tumor Diseases (NCT), Partner Site Dresden, Germany: German Cancer Research Center (DKFZ), Heidelberg, Germany; Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany, and Helmholtz Association/Helmholtz-Zentrum Dresden - Rossendorf (HZDR), Dresden, Germany.,OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany.,German Cancer Research Center (DKFZ), Heidelberg and German Cancer Consortium (DKTK) partner site, Dresden, Germany.,Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiooncology, Dresden, Germany
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Overcast WB, Davis KM, Ho CY, Hutchins GD, Green MA, Graner BD, Veronesi MC. Advanced imaging techniques for neuro-oncologic tumor diagnosis, with an emphasis on PET-MRI imaging of malignant brain tumors. Curr Oncol Rep 2021; 23:34. [PMID: 33599882 PMCID: PMC7892735 DOI: 10.1007/s11912-021-01020-2] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/11/2021] [Indexed: 12/15/2022]
Abstract
PURPOSE OF REVIEW This review will explore the latest in advanced imaging techniques, with a focus on the complementary nature of multiparametric, multimodality imaging using magnetic resonance imaging (MRI) and positron emission tomography (PET). RECENT FINDINGS Advanced MRI techniques including perfusion-weighted imaging (PWI), MR spectroscopy (MRS), diffusion-weighted imaging (DWI), and MR chemical exchange saturation transfer (CEST) offer significant advantages over conventional MR imaging when evaluating tumor extent, predicting grade, and assessing treatment response. PET performed in addition to advanced MRI provides complementary information regarding tumor metabolic properties, particularly when performed simultaneously. 18F-fluoroethyltyrosine (FET) PET improves the specificity of tumor diagnosis and evaluation of post-treatment changes. Incorporation of radiogenomics and machine learning methods further improve advanced imaging. The complementary nature of combining advanced imaging techniques across modalities for brain tumor imaging and incorporating technologies such as radiogenomics has the potential to reshape the landscape in neuro-oncology.
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Affiliation(s)
- Wynton B. Overcast
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 550 N University Blvd. Room 0663, Indianapolis, IN 46202 USA
| | - Korbin M. Davis
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 550 N University Blvd. Room 0663, Indianapolis, IN 46202 USA
| | - Chang Y. Ho
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Goodman Hall, 355 West 16th Street, Suite 4100, Indianapolis, IN 46202 USA
| | - Gary D. Hutchins
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Research 2 Building (R2), Room E124, 920 W. Walnut Street, Indianapolis, IN 46202-5181 USA
| | - Mark A. Green
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Research 2 Building (R2), Room E124, 920 W. Walnut Street, Indianapolis, IN 46202-5181 USA
| | - Brian D. Graner
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Goodman Hall, 355 West 16th Street, Suite 4100, Indianapolis, IN 46202 USA
| | - Michael C. Veronesi
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Research 2 Building (R2), Room E174, 920 W. Walnut Street, Indianapolis, IN 46202-5181 USA
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Decazes P, Hinault P, Veresezan O, Thureau S, Gouel P, Vera P. Trimodality PET/CT/MRI and Radiotherapy: A Mini-Review. Front Oncol 2021; 10:614008. [PMID: 33614497 PMCID: PMC7890017 DOI: 10.3389/fonc.2020.614008] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2020] [Accepted: 12/22/2020] [Indexed: 12/12/2022] Open
Abstract
Computed tomography (CT) has revolutionized external radiotherapy by making it possible to visualize and segment the tumors and the organs at risk in a three-dimensional way. However, if CT is a now a standard, it presents some limitations, notably concerning tumor characterization and delineation. Its association with functional and anatomical images, that are positron emission tomography (PET) and magnetic resonance imaging (MRI), surpasses its limits. This association can be in the form of a trimodality PET/CT/MRI. The objective of this mini-review is to describe the process of performing this PET/CT/MRI trimodality for radiotherapy and its potential clinical applications. Trimodality can be performed in two ways, either a PET/MRI fused to a planning CT (possibly with a pseudo-CT generated from the MRI for the planning), or a PET/CT fused to an MRI and then registered to a planning CT (possibly the CT of PET/CT if calibrated for radiotherapy). These examinations should be performed in the treatment position, and in the second case, a patient transfer system can be used between the PET/CT and MRI to limit movement. If trimodality requires adapted equipment, notably compatible MRI equipment with high-performance dedicated coils, it allows the advantages of the three techniques to be combined with a synergistic effect while limiting their disadvantages when carried out separately. Trimodality is already possible in clinical routine and can have a high clinical impact and good inter-observer agreement, notably for head and neck cancers, brain tumor, prostate cancer, cervical cancer.
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Affiliation(s)
- Pierre Decazes
- Nuclear Medicine Department, Henri Becquerel Cancer Center, Rouen, France.,QuantIF-LITIS EA4108, University of Rouen, Rouen, France
| | | | - Ovidiu Veresezan
- Radiotherapy Department, Henri Becquerel Cancer Center, Rouen, France
| | - Sébastien Thureau
- Nuclear Medicine Department, Henri Becquerel Cancer Center, Rouen, France.,QuantIF-LITIS EA4108, University of Rouen, Rouen, France.,Radiotherapy Department, Henri Becquerel Cancer Center, Rouen, France
| | - Pierrick Gouel
- Nuclear Medicine Department, Henri Becquerel Cancer Center, Rouen, France.,QuantIF-LITIS EA4108, University of Rouen, Rouen, France
| | - Pierre Vera
- Nuclear Medicine Department, Henri Becquerel Cancer Center, Rouen, France.,QuantIF-LITIS EA4108, University of Rouen, Rouen, France
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31
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Comparison of Amino Acid PET to Advanced and Emerging MRI Techniques for Neurooncology Imaging: A Systematic Review of the Recent Studies. Mol Imaging 2021; 2021:8874078. [PMID: 34194287 PMCID: PMC8205602 DOI: 10.1155/2021/8874078] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Revised: 10/23/2020] [Accepted: 11/17/2020] [Indexed: 12/16/2022] Open
Abstract
Introduction Standard neuroimaging protocols for brain tumors have well-known limitations. The clinical use of additional modalities including amino acid PET (aaPET) and advanced MRI (aMRI) techniques (including DWI, PWI, and MRS) is emerging in response to the need for more accurate detection of brain tumors. In this systematic review of the past 2 years of the literature, we discuss the most recent studies that directly compare or combine aaPET and aMRI for brain tumor imaging. Methods A PubMed search was conducted for human studies incorporating both aaPET and aMRI and published between July 2018 and August 2020. Results A total of 22 studies were found in the study period. Recent studies of aaPET with DWI showed a superiority of MET, FET, FDOPA, and AMT PET for detecting tumor, predicting recurrence, diagnosing progression, and predicting survival. Combining modalities further improved performance. Comparisons of aaPET with PWI showed mixed results about spatial correlation. However, both modalities were able to detect high-grade tumors, identify tumor recurrence, differentiate recurrence from treatment effects, and predict survival. aaPET performed better on these measures than PWI, but when combined, they had the strongest results. Studies of aaPET with MRS demonstrated that both modalities have diagnostic potential but MET PET and FDOPA PET performed better than MRS. MRS suffered from some data quality issues that limited analysis in two studies, and, in one study that combined modalities, overall performance actually decreased. Four recent studies compared aaPET with emerging MRI approaches (such as CEST imaging, MR fingerprinting, and SISTINA), but the initial results remain inconclusive. Conclusions aaPET outperformed the aMRI imaging techniques in most recent studies. DWI and PWI added meaningful complementary data, and the combination of aaPET with aMRI yielded the best results in most studies.
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Foray C, Valtorta S, Barca C, Winkeler A, Roll W, Müther M, Wagner S, Gardner ML, Hermann S, Schäfers M, Grauer OM, Moresco RM, Zinnhardt B, Jacobs AH. Imaging temozolomide-induced changes in the myeloid glioma microenvironment. Theranostics 2021; 11:2020-2033. [PMID: 33500706 PMCID: PMC7797694 DOI: 10.7150/thno.47269] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Accepted: 09/21/2020] [Indexed: 12/26/2022] Open
Abstract
Rationale: The heterogeneous nature of gliomas makes the development and application of novel treatments challenging. In particular, infiltrating myeloid cells play a role in tumor progression and therapy resistance. Hence, a detailed understanding of the dynamic interplay of tumor cells and immune cells in vivo is necessary. To investigate the complex interaction between tumor progression and therapy-induced changes in the myeloid immune component of the tumor microenvironment, we used a combination of [18F]FET (amino acid metabolism) and [18F]DPA-714 (TSPO, GAMMs, tumor cells, astrocytes, endothelial cells) PET/MRI together with immune-phenotyping. The aim of the study was to monitor temozolomide (TMZ) treatment response and therapy-induced changes in the inflammatory tumor microenvironment (TME). Methods: Eighteen NMRInu/nu mice orthotopically implanted with Gli36dEGFR cells underwent MRI and PET/CT scans before and after treatment with TMZ or DMSO (vehicle). Tumor-to-background (striatum) uptake ratios were calculated and areas of unique tracer uptake (FET vs. DPA) were determined using an atlas-based volumetric approach. Results: TMZ therapy significantly modified the spatial distribution and uptake of both tracers. [18F]FET uptake was significantly reduced after therapy (-53 ± 84%) accompanied by a significant decrease of tumor volume (-17 ± 6%). In contrast, a significant increase (61 ± 33%) of [18F]DPA-714 uptake was detected by TSPO imaging in specific areas of the tumor. Immunohistochemistry (IHC) validated the reduction in tumor volumes and further revealed the presence of reactive TSPO-expressing glioma-associated microglia/macrophages (GAMMs) in the TME. Conclusion: We confirm the efficiency of [18F]FET-PET for monitoring TMZ-treatment response and demonstrate that in vivo TSPO-PET performed with [18F]DPA-714 can be used to identify specific reactive areas of myeloid cell infiltration in the TME.
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Stadlbauer A, Kinfe TM, Eyüpoglu I, Zimmermann M, Kitzwögerer M, Podar K, Buchfelder M, Heinz G, Oberndorfer S, Marhold F. Tissue Hypoxia and Alterations in Microvascular Architecture Predict Glioblastoma Recurrence in Humans. Clin Cancer Res 2020; 27:1641-1649. [PMID: 33293375 DOI: 10.1158/1078-0432.ccr-20-3580] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Revised: 11/03/2020] [Accepted: 12/04/2020] [Indexed: 11/16/2022]
Abstract
PURPOSE Insufficient control of infiltrative glioblastoma (GBM) cells is a major cause of treatment failure and tumor recurrence. Hence, detailed insights into pathophysiologic changes that precede GBM recurrence are needed to develop more precise neuroimaging modalities for tailored diagnostic monitoring and therapeutic approaches. EXPERIMENTAL DESIGN Overall, 168 physiologic MRI follow-up examinations of 56 patients with GBM who developed recurrence after standard therapy were retrospectively evaluated, that is, two post-standard-therapeutic follow-ups before and one at radiological recurrence. MRI biomarkers for microvascular architecture and perfusion, neovascularization activity, oxygen metabolism, and hypoxia were determined for brain areas that developed in the further course into recurrence and for the recurrent GBM itself. The temporal pattern of biomarker changes was fitted with locally estimated scatterplot smoothing functions and analyzed for pathophysiologic changes preceding radiological GBM recurrence. RESULTS Our MRI approach demonstrated early pathophysiologic changes prior to radiological GBM recurrence in all patients. Analysis of the time courses revealed a model for the pathophysiology of GBM recurrence: 190 days prior to radiological recurrence, vascular cooption by GBM cells induced vessel regression, detected as decreasing vessel density/perfusion and increasing hypoxia. Seventy days later, neovascularization activity was upregulated, which reincreased vessel density and perfusion. Hypoxia, however, continued to intensify for 30 days and peaked 90 days before radiological recurrence. CONCLUSIONS Hypoxia may represent an early sign for GBM recurrence. This might become useful in the development of new combined diagnostic-therapeutic approaches for tailored clinical management of recurrent GBM. Further preclinical and in-human studies are required for validation and evaluation.
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Affiliation(s)
- Andreas Stadlbauer
- Department of Neurosurgery, Friedrich-Alexander University (FAU) Erlangen-Nürnberg, Erlangen, Germany.
- Institute of Medical Radiology, University Clinic St. Pölten, Karl Landsteiner University of Health Sciences, St. Pölten, Austria
| | - Thomas M Kinfe
- Department of Neurosurgery, Friedrich-Alexander University (FAU) Erlangen-Nürnberg, Erlangen, Germany
- Division of Functional Neurosurgery and Stereotaxy, Friedrich-Alexander University (FAU) Erlangen-Nürnberg, Erlangen, Germany
| | - Ilker Eyüpoglu
- Department of Neurosurgery, Friedrich-Alexander University (FAU) Erlangen-Nürnberg, Erlangen, Germany
| | - Max Zimmermann
- Department of Neurosurgery, Friedrich-Alexander University (FAU) Erlangen-Nürnberg, Erlangen, Germany
- Department of Preclinical Imaging and Radiopharmacy, University of Tübingen, Tübingen, Germany
| | - Melitta Kitzwögerer
- Department of Pathology, University Clinic of St. Pölten, St. Pölten, Austria
| | - Klaus Podar
- Department of Internal Medicine 2, University Hospital Krems, Karl Landsteiner University of Health Sciences, Krems, Austria
| | - Michael Buchfelder
- Department of Neurosurgery, Friedrich-Alexander University (FAU) Erlangen-Nürnberg, Erlangen, Germany
| | - Gertraud Heinz
- Institute of Medical Radiology, University Clinic St. Pölten, Karl Landsteiner University of Health Sciences, St. Pölten, Austria
| | - Stefan Oberndorfer
- Department of Neurology, University Clinic of St. Pölten, Karl Landsteiner University of Health Sciences, St. Pölten, Austria
| | - Franz Marhold
- Department of Neurosurgery, University Clinic of St. Pölten, Karl Landsteiner University of Health Sciences, St. Pölten, Austria
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Advanced magnetic resonance imaging to support clinical drug development for malignant glioma. Drug Discov Today 2020; 26:429-441. [PMID: 33249294 DOI: 10.1016/j.drudis.2020.11.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Revised: 10/23/2020] [Accepted: 11/18/2020] [Indexed: 11/22/2022]
Abstract
Even though the treatment options and survival of patients with glioblastoma multiforme (GBM), the most common type of malignant glioma, have improved over the past decade, there is still a high unmet medical need to develop novel therapies. Complexity in pathology and therapy require biomarkers to characterize tumors, to define malignant and active areas, to assess disease prognosis, and to quantify and monitor therapy response. While conventional magnetic resonance imaging (MRI) techniques have improved these assessments, limitations remain. In this review, we evaluate the role of various non-invasive biomarkers based on advanced structural and functional MRI techniques in the context of GBM drug development over the past 5 years.
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Soni N, Ora M, Mohindra N, Menda Y, Bathla G. Diagnostic Performance of PET and Perfusion-Weighted Imaging in Differentiating Tumor Recurrence or Progression from Radiation Necrosis in Posttreatment Gliomas: A Review of Literature. AJNR Am J Neuroradiol 2020; 41:1550-1557. [PMID: 32855194 DOI: 10.3174/ajnr.a6685] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Accepted: 05/29/2020] [Indexed: 01/22/2023]
Abstract
Tumor resection followed by chemoradiation remains the current criterion standard treatment for high-grade gliomas. Regardless of aggressive treatment, tumor recurrence and radiation necrosis are 2 different outcomes. Differentiation of tumor recurrence from radiation necrosis remains a critical problem in these patients because of considerable overlap in clinical and imaging presentations. Contrast-enhanced MR imaging is the universal imaging technique for diagnosis, treatment evaluation, and detection of recurrence of high-grade gliomas. PWI and PET with novel radiotracers have an evolving role for monitoring treatment response in high-grade gliomas. In the literature, there is no clear consensus on the superiority of either technique or their complementary information. This review aims to elucidate the diagnostic performance of individual and combined use of functional (PWI) and metabolic (PET) imaging modalities to distinguish recurrence from posttreatment changes in gliomas.
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Affiliation(s)
- N Soni
- Department of Radiology (N.S., Y.M., G.B.), University of Iowa Hospitals and Clinics, Iowa City, Iowa
| | - M Ora
- Department of Radiodiagnosis (M.O., N.M.), Sanjay Gandhi Post Graduate Institute of Medical Sciences, Institute of Nuclear Medicine, Lucknow, India
| | - N Mohindra
- Department of Radiodiagnosis (M.O., N.M.), Sanjay Gandhi Post Graduate Institute of Medical Sciences, Institute of Nuclear Medicine, Lucknow, India
| | - Y Menda
- Department of Radiology (N.S., Y.M., G.B.), University of Iowa Hospitals and Clinics, Iowa City, Iowa
| | - G Bathla
- Department of Radiology (N.S., Y.M., G.B.), University of Iowa Hospitals and Clinics, Iowa City, Iowa
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Quartuccio N, Laudicella R, Vento A, Pignata S, Mattoli MV, Filice R, Comis AD, Arnone A, Baldari S, Cabria M, Cistaro A. The Additional Value of 18F-FDG PET and MRI in Patients with Glioma: A Review of the Literature from 2015 to 2020. Diagnostics (Basel) 2020; 10:diagnostics10060357. [PMID: 32486075 PMCID: PMC7345880 DOI: 10.3390/diagnostics10060357] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Revised: 05/15/2020] [Accepted: 05/27/2020] [Indexed: 02/07/2023] Open
Abstract
AIM Beyond brain computed tomography (CT) scan, Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) hold paramount importance in neuro-oncology. The aim of this narrative review is to discuss the literature from 2015 to 2020, showing advantages or complementary information of fluorine-18 fluorodeoxyglucose (18F-FDG) PET imaging to the anatomical and functional data offered by MRI in patients with glioma. METHODS A comprehensive Pubmed/MEDLINE literature search was performed to retrieve original studies, with a minimum of 10 glioma patients, published from 2015 until the end of April 2020, on the use of 18F-FDG PET in conjunction with MRI. RESULTS Twenty-two articles were selected. Combined use of the two modalities improves the accuracy in predicting prognosis, planning treatments, and evaluating recurrence. CONCLUSION According to the recent literature, 18F-FDG PET provides different and complementary information to MRI and may enhance performance in the whole management of gliomas. Therefore, integrated PET/MRI may be particularly useful in gliomas, since it could provide accurate morphological and metabolic information in one-shoot examination and improve the diagnostic value compared to each of procedures.
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Affiliation(s)
- Natale Quartuccio
- Nuclear Medicine Unit, A.R.N.A.S. Ospedali Civico, Di Cristina e Benfratelli, 90127 Palermo, Italy; (N.Q.); (A.A.)
- Committee of AIMN Pediatric Study Group, 20159 Milan, Italy
| | - Riccardo Laudicella
- Nuclear Medicine Unit, Department of Biomedical and Dental Sciences and Morpho-Functional Imaging, University of Messina, 98125 Messina, Italy; (R.L.); (A.V.); (S.P.); (R.F.); (A.D.C.); (S.B.)
- AIMN -Italian Association of Nuclear Medicine- Young Members Working Group, 20159 Milan, Italy
| | - Antonio Vento
- Nuclear Medicine Unit, Department of Biomedical and Dental Sciences and Morpho-Functional Imaging, University of Messina, 98125 Messina, Italy; (R.L.); (A.V.); (S.P.); (R.F.); (A.D.C.); (S.B.)
| | - Salvatore Pignata
- Nuclear Medicine Unit, Department of Biomedical and Dental Sciences and Morpho-Functional Imaging, University of Messina, 98125 Messina, Italy; (R.L.); (A.V.); (S.P.); (R.F.); (A.D.C.); (S.B.)
| | - Maria Vittoria Mattoli
- Department of Neurosciences, Imaging and Clinical Sciences, “G. d’Annunzio” University, 66100 Chieti, Italy;
| | - Rossella Filice
- Nuclear Medicine Unit, Department of Biomedical and Dental Sciences and Morpho-Functional Imaging, University of Messina, 98125 Messina, Italy; (R.L.); (A.V.); (S.P.); (R.F.); (A.D.C.); (S.B.)
| | - Alessio Danilo Comis
- Nuclear Medicine Unit, Department of Biomedical and Dental Sciences and Morpho-Functional Imaging, University of Messina, 98125 Messina, Italy; (R.L.); (A.V.); (S.P.); (R.F.); (A.D.C.); (S.B.)
| | - Annachiara Arnone
- Nuclear Medicine Unit, A.R.N.A.S. Ospedali Civico, Di Cristina e Benfratelli, 90127 Palermo, Italy; (N.Q.); (A.A.)
| | - Sergio Baldari
- Nuclear Medicine Unit, Department of Biomedical and Dental Sciences and Morpho-Functional Imaging, University of Messina, 98125 Messina, Italy; (R.L.); (A.V.); (S.P.); (R.F.); (A.D.C.); (S.B.)
| | - Manlio Cabria
- Nuclear Medicine Department, Ente Ospedaliero Ospedali Galliera, Italy, Mura delle Cappuccine, 14, 16128 Genova, Italy;
| | - Angelina Cistaro
- Nuclear Medicine Department, Ente Ospedaliero Ospedali Galliera, Italy, Mura delle Cappuccine, 14, 16128 Genova, Italy;
- Committee of AIMN Neuroimaging Study Group, 20159 Milan, Italy
- Coordinator of AIMN Paediatric Study Group, 20159 Milan, Italy
- Correspondence: ; Tel.: +39-22254881
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Unterrainer M, Eze C, Ilhan H, Marschner S, Roengvoraphoj O, Schmidt-Hegemann NS, Walter F, Kunz WG, Rosenschöld PMA, Jeraj R, Albert NL, Grosu AL, Niyazi M, Bartenstein P, Belka C. Recent advances of PET imaging in clinical radiation oncology. Radiat Oncol 2020; 15:88. [PMID: 32317029 PMCID: PMC7171749 DOI: 10.1186/s13014-020-01519-1] [Citation(s) in RCA: 64] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2020] [Accepted: 03/19/2020] [Indexed: 12/25/2022] Open
Abstract
Radiotherapy and radiation oncology play a key role in the clinical management of patients suffering from oncological diseases. In clinical routine, anatomic imaging such as contrast-enhanced CT and MRI are widely available and are usually used to improve the target volume delineation for subsequent radiotherapy. Moreover, these modalities are also used for treatment monitoring after radiotherapy. However, some diagnostic questions cannot be sufficiently addressed by the mere use standard morphological imaging. Therefore, positron emission tomography (PET) imaging gains increasing clinical significance in the management of oncological patients undergoing radiotherapy, as PET allows the visualization and quantification of tumoral features on a molecular level beyond the mere morphological extent shown by conventional imaging, such as tumor metabolism or receptor expression. The tumor metabolism or receptor expression information derived from PET can be used as tool for visualization of tumor extent, for assessing response during and after therapy, for prediction of patterns of failure and for definition of the volume in need of dose-escalation. This review focuses on recent and current advances of PET imaging within the field of clinical radiotherapy / radiation oncology in several oncological entities (neuro-oncology, head & neck cancer, lung cancer, gastrointestinal tumors and prostate cancer) with particular emphasis on radiotherapy planning, response assessment after radiotherapy and prognostication.
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Affiliation(s)
- M Unterrainer
- Department of Nuclear Medicine, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany. .,Department of Radiology, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany. .,German Cancer Consortium (DKTK), partner site Munich; and German Cancer Research Center (DKFZ), Heidelberg, Germany.
| | - C Eze
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - H Ilhan
- Department of Nuclear Medicine, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany
| | - S Marschner
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - O Roengvoraphoj
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - N S Schmidt-Hegemann
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - F Walter
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - W G Kunz
- Department of Radiology, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany
| | - P Munck Af Rosenschöld
- Radiation Physics, Department of Hematology, Oncology and Radiation Physics, Skåne University Hospital, and Lund University, Lund, Sweden
| | - R Jeraj
- Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, USA
| | - N L Albert
- Department of Nuclear Medicine, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.,German Cancer Consortium (DKTK), partner site Munich; and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - A L Grosu
- Department of Radiation Oncology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.,German Cancer Consortium (DKTK), partner Site Freiburg, Freiburg, Germany
| | - M Niyazi
- German Cancer Consortium (DKTK), partner site Munich; and German Cancer Research Center (DKFZ), Heidelberg, Germany.,Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - P Bartenstein
- Department of Nuclear Medicine, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.,German Cancer Consortium (DKTK), partner site Munich; and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - C Belka
- German Cancer Consortium (DKTK), partner site Munich; and German Cancer Research Center (DKFZ), Heidelberg, Germany.,Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
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Detection of Glioblastoma Subclinical Recurrence Using Serial Diffusion Tensor Imaging. Cancers (Basel) 2020; 12:cancers12030568. [PMID: 32121471 PMCID: PMC7139975 DOI: 10.3390/cancers12030568] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2019] [Revised: 02/27/2020] [Accepted: 02/27/2020] [Indexed: 12/31/2022] Open
Abstract
Glioblastoma is an aggressive brain tumor with a propensity for intracranial recurrence. We hypothesized that tumors can be visualized with diffusion tensor imaging (DTI) before they are detected on anatomical magnetic resonance (MR) images. We retrospectively analyzed serial MR images from 30 patients, including the DTI and T1-weighted images at recurrence, at 2 months and 4 months before recurrence, and at 1 month after radiation therapy. The diffusion maps and T1 images were deformably registered longitudinally. The recurrent tumor was manually segmented on the T1-weighted image and then applied to the diffusion maps at each time point to collect mean FA, diffusivities, and neurite density index (NDI) values, respectively. Group analysis of variance showed significant changes in FA (p = 0.01) and NDI (p = 0.0015) over time. Pairwise t tests also revealed that FA and NDI at 2 months before recurrence were 11.2% and 6.4% lower than those at 1 month after radiation therapy (p < 0.05), respectively. Changes in FA and NDI were observed 2 months before recurrence, suggesting that progressive microstructural changes and neurite density loss may be detectable before tumor detection in anatomical MR images. FA and NDI may serve as non-contrast MR-based biomarkers for detecting subclinical tumors.
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Foray C, Barca C, Backhaus P, Schelhaas S, Winkeler A, Viel T, Schäfers M, Grauer O, Jacobs AH, Zinnhardt B. Multimodal Molecular Imaging of the Tumour Microenvironment. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2020; 1225:71-87. [PMID: 32030648 DOI: 10.1007/978-3-030-35727-6_5] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
The tumour microenvironment (TME) surrounding tumour cells is a highly dynamic and heterogeneous composition of immune cells, fibroblasts, precursor cells, endothelial cells, signalling molecules and extracellular matrix (ECM) components. Due to the heterogeneity and the constant crosstalk between the TME and the tumour cells, the components of the TME are important prognostic parameters in cancer and determine the response to novel immunotherapies. To improve the characterization of the TME, novel non-invasive imaging paradigms targeting the complexity of the TME are urgently needed.The characterization of the TME by molecular imaging will (1) support early diagnosis and disease follow-up, (2) guide (stereotactic) biopsy sampling, (3) highlight the dynamic changes during disease pathogenesis in a non-invasive manner, (4) help monitor existing therapies, (5) support the development of novel TME-targeting therapies and (6) aid stratification of patients, according to the cellular composition of their tumours in correlation to their therapy response.This chapter will summarize the most recent developments and applications of molecular imaging paradigms beyond FDG for the characterization of the dynamic molecular and cellular changes in the TME.
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Affiliation(s)
- Claudia Foray
- European Institute for Molecular Imaging (EIMI), University of Münster, Münster, Germany.,PET Imaging in Drug Design and Development (PET3D), Münster, Germany
| | - Cristina Barca
- European Institute for Molecular Imaging (EIMI), University of Münster, Münster, Germany.,PET Imaging in Drug Design and Development (PET3D), Münster, Germany
| | - Philipp Backhaus
- European Institute for Molecular Imaging (EIMI), University of Münster, Münster, Germany.,Department of Nuclear Medicine, University Hospital Münster, Westfälische Wilhelms University Münster, Münster, Germany
| | - Sonja Schelhaas
- European Institute for Molecular Imaging (EIMI), University of Münster, Münster, Germany
| | - Alexandra Winkeler
- UMR 1023, IMIV, Service Hospitalier Frédéric Joliot, CEA, Inserm, Université Paris Sud, CNRS, Université Paris-Saclay, Orsay, France
| | - Thomas Viel
- Paris Centre de Recherche Cardiovasculaire, INSERM-U970, Université Paris Descartes, Paris, France
| | - Michael Schäfers
- European Institute for Molecular Imaging (EIMI), University of Münster, Münster, Germany.,Department of Nuclear Medicine, University Hospital Münster, Westfälische Wilhelms University Münster, Münster, Germany
| | - Oliver Grauer
- Department of Neurology, University Hospital Münster, Münster, Germany
| | - Andreas H Jacobs
- European Institute for Molecular Imaging (EIMI), University of Münster, Münster, Germany.,PET Imaging in Drug Design and Development (PET3D), Münster, Germany.,Department of Geriatrics, Johanniter Hospital, Evangelische Kliniken, Bonn, Germany
| | - Bastian Zinnhardt
- European Institute for Molecular Imaging (EIMI), University of Münster, Münster, Germany. .,PET Imaging in Drug Design and Development (PET3D), Münster, Germany. .,Department of Nuclear Medicine, University Hospital Münster, Westfälische Wilhelms University Münster, Münster, Germany.
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