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Wang H, Zeng L, Wu H, Tian J, Xie H, Zhang L, Ran Q, Zhong P, Chen L, Yi L, Wang S. Preoperative vascular heterogeneity based on dynamic susceptibility contrast MRI in predicting spatial pattern of locally recurrent high-grade gliomas. Eur Radiol 2024; 34:1982-1993. [PMID: 37658897 PMCID: PMC10873240 DOI: 10.1007/s00330-023-10149-6] [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: 12/09/2022] [Revised: 06/15/2023] [Accepted: 07/06/2023] [Indexed: 09/05/2023]
Abstract
OBJECTIVES To investigate if spatial recurrence pattern is associated with patient prognosis, and whether MRI vascular habitats can predict spatial pattern. METHODS In this retrospective study, 69 patients with locally recurrent high-grade gliomas (HGGs) were included. The cohort was divided into intra-resection cavity recurrence (ICR) and extra-resection cavity recurrence (ECR) patterns, according to the distance between the location of the recurrent tumor and the resection cavity or surgical region. Four vascular habitats, high angiogenic tumor, low angiogenic tumor, infiltrated peripheral edema, and vasogenic peripheral edema, were segmented and vascular heterogeneity parameters were analyzed. The survival and diagnostic performance under different spatial recurrence patterns were analyzed by Kaplan-Meier and ROC. A nomogram model was constructed by regression analysis and validated by bootstrapping technique. RESULTS Progression-free survival (PFS) and overall survival (OS) were longer for ICR (n = 32) than those for ECR (n = 37) (median PFS: 8 vs. 5 months, median OS: 17 vs. 13 months, p < 0.05). MRI vascular habitat analyses showed ECR had higher median relative cerebral blood volume (rCBVmedian) at each habitat than ICR (all p < 0.01). The rCBVmedian at IPE had good diagnostic performance (AUC: 0.727, 95%CI: 0.607, 0.828). The AUC of the nomogram based on MRI vascular habitats and clinical factors was 0.834 (95%CI: 0.726, 0.913) and was confirmed as 0.833 (95%CI: 0.830, 0.836) by bootstrapping validation. CONCLUSIONS The spatial pattern of locally recurrent HGGs is associated with prognosis. MRI vascular heterogeneity parameter could be used as a non-invasive imaging marker to predict spatial recurrence pattern. CLINICAL RELEVANCE STATEMENT Vascular heterogeneity parameters based on MRI vascular habitat analyses can non-invasively predict the spatial patterns of locally recurrent high-grade gliomas, providing a new diagnostic basis for clinicians to develop the extent of surgical resection and postoperative radiotherapy planning. KEY POINTS • Intra-resection cavity pattern was associated with longer progression-free survival and overall survival in locally recurrent high-grade gliomas. • Higher vascular heterogeneities in extra-resection cavity recurrence than in intra-resection cavity recurrence and the vascular heterogeneity parameters had good diagnostic performance in discriminating spatial recurrence pattern. • A nomogram model based on MRI vascular habitats and clinical factors had good performance in predicting spatial recurrence pattern.
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Affiliation(s)
- Hanwei Wang
- Department of Radiology, Daping Hospital, Army Medical University, Chongqing, China
- Chongqing Clinical Research Center of Imaging and Nuclear Medicine, Chongqing, China
| | - Linlan Zeng
- Department of Radiology, Daping Hospital, Army Medical University, Chongqing, China
- Chongqing Clinical Research Center of Imaging and Nuclear Medicine, Chongqing, China
| | - Hao Wu
- Department of Radiology, Daping Hospital, Army Medical University, Chongqing, China
- Chongqing Clinical Research Center of Imaging and Nuclear Medicine, Chongqing, China
| | - Jing Tian
- Department of Radiology, Daping Hospital, Army Medical University, Chongqing, China
- Chongqing Clinical Research Center of Imaging and Nuclear Medicine, Chongqing, China
| | - Huan Xie
- Department of Radiology, Daping Hospital, Army Medical University, Chongqing, China
- Chongqing Clinical Research Center of Imaging and Nuclear Medicine, Chongqing, China
| | - Letian Zhang
- Department of Radiology, Daping Hospital, Army Medical University, Chongqing, China
- Chongqing Clinical Research Center of Imaging and Nuclear Medicine, Chongqing, China
| | - Qisheng Ran
- Department of Radiology, Daping Hospital, Army Medical University, Chongqing, China
- Chongqing Clinical Research Center of Imaging and Nuclear Medicine, Chongqing, China
| | - Peng Zhong
- Department of Pathology, Daping Hospital, Army Medical University, Chongqing, China
| | - Lizhao Chen
- Department of Neurosurgery, Daping Hospital, Army Medical University, Chongqing, China
| | - Liang Yi
- Department of Neurosurgery, Daping Hospital, Army Medical University, Chongqing, China.
| | - Shunan Wang
- Department of Radiology, Daping Hospital, Army Medical University, Chongqing, China.
- Chongqing Clinical Research Center of Imaging and Nuclear Medicine, Chongqing, China.
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Fariña-Jerónimo H, Martín-Ramírez R, González-Fernández R, Medina L, de Vera A, Martín-Vasallo P, Plata-Bello J. Androgen deficiency is associated with a better prognosis in glioblastoma. Eur J Med Res 2024; 29:57. [PMID: 38233838 DOI: 10.1186/s40001-024-01648-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Accepted: 01/07/2024] [Indexed: 01/19/2024] Open
Abstract
BACKGROUND The androgen receptor (AR) has been demonstrated to play a role in the pathogenesis of glioblastoma; however, the implications of circulating testosterone levels in the biology of glioblastoma remain unknown. AIM This study aimed to analyze the association between circulating testosterone levels and the prognosis of patients with glioblastoma. METHODS Forty patients with primary glioblastoma were included in the study. The main prognostic endpoint was progression-free survival (PFS). Circulating testosterone levels were used to determine the state of androgen deficiency (AD). AR expression was analyzed by reverse-transcriptase polymerase chain reaction, Western blot, and immunofluorescence. Survival analysis was performed using the log-rank test and univariate and multivariate Cox regression analysis. RESULTS Most of the patients showed AR expression, and it was mainly located in the cytoplasm, as well as in the nucleus of tumor cells. Patients with AD presented a better PFS than those patients with normal levels (252.0 vs. 135.0 days; p = 0.041). Furthermore, normal androgenic status was an independent risk factor for progression in a multivariate regression model (hazard ratio = 6.346; p = 0.004). CONCLUSION Circulating testosterone levels are associated with the prognosis of glioblastoma because patients with AD show a better prognosis than those with normal androgenic status.
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Affiliation(s)
- Helga Fariña-Jerónimo
- Neurosurgery Department, Hospital Universitario de Canarias, Calle Ofra s/n La Cuesta, CP 38320, La Laguna, S/C de Tenerife, Spain
| | | | | | - Lilian Medina
- Biochemistry Laboratory, Hospital Universitario de Canarias, La Laguna, Spain
| | - Antonia de Vera
- Biochemistry Laboratory, Hospital Universitario de Canarias, La Laguna, Spain
| | | | - Julio Plata-Bello
- Neurosurgery Department, Hospital Universitario de Canarias, Calle Ofra s/n La Cuesta, CP 38320, La Laguna, S/C de Tenerife, Spain.
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Prysiazhniuk Y, Server A, Leske H, Bech-Aase Ø, Helseth E, Eijgelaar RS, Fuster-García E, Brandal P, Bjørnerud A, Otáhal J, Petr J, Nordhøy W. Diffuse glioma molecular profiling with arterial spin labeling and dynamic susceptibility contrast perfusion MRI: A comparative study. Neurooncol Adv 2024; 6:vdae113. [PMID: 39036439 PMCID: PMC11259011 DOI: 10.1093/noajnl/vdae113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/23/2024] Open
Abstract
Background Evaluation of molecular markers (IDH, pTERT, 1p/19q codeletion, and MGMT) in adult diffuse gliomas is crucial for accurate diagnosis and optimal treatment planning. Dynamic Susceptibility Contrast (DSC) and Arterial Spin Labeling (ASL) perfusion MRI techniques have both shown good performance in classifying molecular markers, however, their performance has not been compared side-by-side. Methods Pretreatment MRI data from 90 patients diagnosed with diffuse glioma (54 men/36 female, 53.1 ± 15.5 years, grades 2-4) were retrospectively analyzed. DSC-derived normalized cerebral blood flow/volume (nCBF/nCBV) and ASL-derived nCBF in tumor and perifocal edema were analyzed in patients with available IDH-mutation (n = 67), pTERT-mutation (n = 39), 1p/19q codeletion (n = 33), and MGMT promoter methylation (n = 31) status. Cross-validated uni- and multivariate logistic regression models assessed perfusion parameters' performance in molecular marker detection. Results ASL and DSC perfusion parameters in tumor and edema distinguished IDH-wildtype (wt) and pTERT-wt tumors from mutated ones. Univariate classification performance was comparable for ASL-nCBF and DSC-nCBV in IDH (maximum AUROCC 0.82 and 0.83, respectively) and pTERT (maximum AUROCC 0.70 and 0.81, respectively) status differentiation. The multivariate approach improved IDH (DSC-nCBV AUROCC 0.89) and pTERT (ASL-nCBF AUROCC 0.8 and DSC-nCBV AUROCC 0.86) classification. However, ASL and DSC parameters could not differentiate 1p/19q codeletion or MGMT promoter methylation status. Positive correlations were found between ASL-nCBF and DSC-nCBV/-nCBF in tumor and edema. Conclusions ASL is a viable gadolinium-free replacement for DSC for molecular characterization of adult diffuse gliomas.
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Affiliation(s)
- Yeva Prysiazhniuk
- Department of Pathophysiology, Second Faculty of Medicine, Charles University, Prague, The Czech Republic
| | - Andres Server
- Section of Neuroradiology, Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Henning Leske
- Department of Pathology, Oslo University Hospital, Oslo, Norway
| | - Øystein Bech-Aase
- Department of Physics and Computational Radiology, Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Eirik Helseth
- Department of Neurosurgery, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | | | - Elies Fuster-García
- Biomedical Data Science Laboratory, Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de València, València, Spain
| | - Petter Brandal
- Department of Oncology, Oslo University Hospital, Oslo, Norway
- Section for Cancer Cytogenetics, Institute for Cancer Genetics and Informatics, Oslo University Hospital, Oslo, Norway
| | - Atle Bjørnerud
- Department of Physics and Computational Radiology, Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
| | - Jakub Otáhal
- Department of Pathophysiology, Second Faculty of Medicine, Charles University, Prague, The Czech Republic
| | - Jan Petr
- Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Location VUmc, Amsterdam, The Netherlands
| | - Wibeke Nordhøy
- Department of Physics and Computational Radiology, Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
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Álvarez-Torres MDM, Balaña C, Fuster-García E, Puig J, García-Gómez JM. Unlocking Bevacizumab's Potential: rCBV max as a Predictive Biomarker for Enhanced Survival in Glioblastoma IDH-Wildtype Patients. Cancers (Basel) 2023; 16:161. [PMID: 38201588 PMCID: PMC10778147 DOI: 10.3390/cancers16010161] [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: 12/13/2023] [Revised: 12/27/2023] [Accepted: 12/27/2023] [Indexed: 01/12/2024] Open
Abstract
BACKGROUND Aberrant vascular architecture and angiogenesis are hallmarks of glioblastoma IDH-wildtype, suggesting that these tumors are suitable for antiangiogenic therapy. Bevacizumab was FDA-approved in 2009 following promising results in two clinical trials. However, its use for recurrent glioblastomas remains a subject of debate, as it does not universally improve patient survival. PURPOSES In this study, we aimed to analyze the influence of tumor vascularity on the benefit provided by BVZ and propose preoperative rCBVmax at the high angiogenic tumor habitat as a predictive biomarker to select patients who can benefit the most. METHODS Clinical and MRI data from 106 patients with glioblastoma IDH-wildtype have been analyzed. Thirty-nine of them received BVZ, and the remaining sixty-seven did not receive a second-line treatment. The ONCOhabitats method was used to automatically calculate rCBV. RESULTS We found a median survival from progression of 305 days longer for patients with moderate vascular tumors who received BVZ than those who did not receive any second-line treatment. This contrasts with patients with high-vascular tumors who only presented a median survival of 173 days longer when receiving BVZ. Furthermore, better responses to BVZ were found for the moderate-vascular group with a higher proportion of patients alive at 6, 12, 18, and 24 months after progression. CONCLUSIONS We propose rCBVmax as a potential biomarker to select patients who can benefit more from BVZ after tumor progression. In addition, we propose a threshold of 7.5 to stratify patients into moderate- and high-vascular groups to select the optimal second-line treatment.
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Affiliation(s)
- María del Mar Álvarez-Torres
- Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de Valencia, 46022 Valencia, Spain; (E.F.-G.); (J.M.G.-G.)
| | - Carmen Balaña
- Applied Research Group in Oncology (B-ARGO Group), Institut Catala d’Oncologia (ICO), Institut Investigació Germans Trias i Pujol (IGTP), 08916 Badalona, Spain;
| | - Elies Fuster-García
- Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de Valencia, 46022 Valencia, Spain; (E.F.-G.); (J.M.G.-G.)
| | - Josep Puig
- Radiology Department CDI, Hospital Clinic of Barcelona, 08036 Barcelona, Spain;
| | - Juan Miguel García-Gómez
- Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de Valencia, 46022 Valencia, Spain; (E.F.-G.); (J.M.G.-G.)
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Liouta E, Koutsarnakis C, Komaitis S, Kalyvas AV, Drosos E, García-Gómez JM, Juan-Albarracín J, Katsaros V, Stavrinou L, Stranjalis G. Preoperative neurocognitive function as an independent survival prognostic marker in primary glioblastoma. Neurooncol Pract 2023; 10:527-535. [PMID: 38026584 PMCID: PMC10666798 DOI: 10.1093/nop/npad027] [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] [Indexed: 12/01/2023] Open
Abstract
Background Aim of the present study is to investigate whether preoperative neurocognitive status is prognostically associated with overall survival (OS) in newly diagnosed glioblastoma (GBM) patients. Methods Ninety patients with dominant-hemisphere IDH-wild-type GBM were assessed by Mini Mental Status Exam (MMSE), Trail Making Test (TMT) A and B parts, and Control Word Association Test (COWAT) phonemic and semantic subtests. Demographics, Karnofsky Performance Scale, tumor parameters, type of surgery, and adjuvant therapy data were available for patients. Results According to Cox proportional hazards model the neurocognitive variables of TMT B (P < .01), COWAT semantic subset (P < .05), and the MMSE (P < .01) were found significantly associated with survival prediction. From all other factors, only tumor volume and operation type (debulking vs biopsy) showed a statistical association (P < .05) with survival prediction. Kaplan Meier Long rank test showed statistical significance (P < .01) between unimpaired and impaired groups for TMT B, with median survival for the unimpaired group 26 months and 10 months for the impaired group, for COWAT semantic (P < .01) with median survival 23 months and 12 months, respectively and for MMSE (P < .01) with medial survival 19 and 12 months respectively. Conclusions Our study demonstrates that neurocognitive status at baseline-prior to treatment-is an independent prognostic factor for OS in wild-type GBM patients, adding another prognostic tool to assist physicians in selecting the best treatment plan.
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Affiliation(s)
- Evangelia Liouta
- 1st Department of Neurosurgery, National and Kapodistrian University of Athens, Evangelismos Hospital, Athens, Greece
- Hellenic Center for Neurosurgical Research “Prof. Petros Kokkalis,”Athens, Greece
| | - Christos Koutsarnakis
- 1st Department of Neurosurgery, National and Kapodistrian University of Athens, Evangelismos Hospital, Athens, Greece
- Athens Microneurosurgery Laboratory, Grupo de Informática Biomédica (IBIME), Instituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas (ITACA), Universitat Politècnica de València, Valencia, Spain
| | - Spyridon Komaitis
- 1st Department of Neurosurgery, National and Kapodistrian University of Athens, Evangelismos Hospital, Athens, Greece
- Athens Microneurosurgery Laboratory, Grupo de Informática Biomédica (IBIME), Instituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas (ITACA), Universitat Politècnica de València, Valencia, Spain
| | - Aristotelis V Kalyvas
- 1st Department of Neurosurgery, National and Kapodistrian University of Athens, Evangelismos Hospital, Athens, Greece
- Athens Microneurosurgery Laboratory, Grupo de Informática Biomédica (IBIME), Instituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas (ITACA), Universitat Politècnica de València, Valencia, Spain
| | - Evangelos Drosos
- 1st Department of Neurosurgery, National and Kapodistrian University of Athens, Evangelismos Hospital, Athens, Greece
- Athens Microneurosurgery Laboratory, Grupo de Informática Biomédica (IBIME), Instituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas (ITACA), Universitat Politècnica de València, Valencia, Spain
| | - Juan M García-Gómez
- Athens Microneurosurgery Laboratory, Grupo de Informática Biomédica (IBIME), Instituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas (ITACA), Universitat Politècnica de València, Valencia, Spain
| | - Javier Juan-Albarracín
- Athens Microneurosurgery Laboratory, Grupo de Informática Biomédica (IBIME), Instituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas (ITACA), Universitat Politècnica de València, Valencia, Spain
| | - Vasileios Katsaros
- Department of Radiology, General Anti-Cancer and Oncological Hospital of Athens “St. Savvas”, Athens, Greece
| | - Lampis Stavrinou
- 2nd Department of Neurosurgery, National and Kapodistrian University of Athens, ATTIKO Hospital, Athens, Greece
| | - George Stranjalis
- 1st Department of Neurosurgery, National and Kapodistrian University of Athens, Evangelismos Hospital, Athens, Greece
- Hellenic Center for Neurosurgical Research “Prof. Petros Kokkalis,”Athens, Greece
- Athens Microneurosurgery Laboratory, Grupo de Informática Biomédica (IBIME), Instituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas (ITACA), Universitat Politècnica de València, Valencia, Spain
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Álvarez-Torres MDM, López-Cerdán A, Andreu Z, de la Iglesia Vayá M, Fuster-Garcia E, García-García F, García-Gómez JM. Vascular differences between IDH-wildtype glioblastoma and astrocytoma IDH-mutant grade 4 at imaging and transcriptomic levels. NMR IN BIOMEDICINE 2023; 36:e5004. [PMID: 37482922 DOI: 10.1002/nbm.5004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 05/31/2023] [Accepted: 06/23/2023] [Indexed: 07/25/2023]
Abstract
Global agreement in central nervous system (CNS) tumor classification is essential for predicting patient prognosis and determining the correct course of treatment, as well as for stratifying patients for clinical trials at international level. The last update by the World Health Organization of CNS tumor classification and grading in 2021 considered, for the first time, IDH-wildtype glioblastoma and astrocytoma IDH-mutant grade 4 as different tumors. Mutations in the genes isocitrate dehydrogenase (IDH) 1 and 2 occur early and, importantly, contribute to gliomagenesis. IDH mutation produces a metabolic reprogramming of tumor cells, thus affecting the processes of hypoxia and vascularity, resulting in a clear advantage for those patients who present with IDH-mutated astrocytomas. Despite the clinical relevance of IDH mutation, current protocols do not include full sequencing for every patient. Alternative biomarkers could be useful and complementary to obtain a more reliable classification. In this sense, magnetic resonance imaging (MRI)-perfusion biomarkers, such as relative cerebral blood volume and flow, could be useful from the moment of presurgery, without incurring additional financial costs or requiring extra effort. The main purpose of this work is to analyze the vascular and hemodynamic differences between IDH-wildtype glioblastoma and IDH-mutant astrocytoma. To achieve this, we evaluate and validate the association between dynamic susceptibility contrast-MRI perfusion biomarkers and IDH mutation status. In addition, to gain a deeper understanding of the vascular differences in astrocytomas depending on the IDH mutation, we analyze the transcriptomic bases of the vascular differences.
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Affiliation(s)
- María Del Mar Álvarez-Torres
- Biomedical Data Science Laboratory, ITACA (Instituto de Información y Tecnología de las Comunicaciones), Universitat Politècnica de València, Valencia, Spain
| | - Adolfo López-Cerdán
- Unidad Mixta de Imagen Biomédica FISABIO-CIPF (Centro Investigación Príncipe Felipe), Valencia, Spain
| | - Zoraida Andreu
- Foundation Valencian Institute of Oncology (FIVO), Valencia, Spain
| | - Maria de la Iglesia Vayá
- Unidad Mixta de Imagen Biomédica FISABIO-CIPF (Centro Investigación Príncipe Felipe), Valencia, Spain
| | - Elies Fuster-Garcia
- Biomedical Data Science Laboratory, ITACA (Instituto de Información y Tecnología de las Comunicaciones), Universitat Politècnica de València, Valencia, Spain
| | | | - Juan M García-Gómez
- Biomedical Data Science Laboratory, ITACA (Instituto de Información y Tecnología de las Comunicaciones), Universitat Politècnica de València, Valencia, Spain
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Waqar M, Van Houdt PJ, Hessen E, Li KL, Zhu X, Jackson A, Iqbal M, O’Connor J, Djoukhadar I, van der Heide UA, Coope DJ, Borst GR. Visualising spatial heterogeneity in glioblastoma using imaging habitats. Front Oncol 2022; 12:1037896. [PMID: 36505856 PMCID: PMC9731157 DOI: 10.3389/fonc.2022.1037896] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 10/31/2022] [Indexed: 11/26/2022] Open
Abstract
Glioblastoma is a high-grade aggressive neoplasm characterised by significant intra-tumoral spatial heterogeneity. Personalising therapy for this tumour requires non-invasive tools to visualise its heterogeneity to monitor treatment response on a regional level. To date, efforts to characterise glioblastoma's imaging features and heterogeneity have focussed on individual imaging biomarkers, or high-throughput radiomic approaches that consider a vast number of imaging variables across the tumour as a whole. Habitat imaging is a novel approach to cancer imaging that identifies tumour regions or 'habitats' based on shared imaging characteristics, usually defined using multiple imaging biomarkers. Habitat imaging reflects the evolution of imaging biomarkers and offers spatially preserved assessment of tumour physiological processes such perfusion and cellularity. This allows for regional assessment of treatment response to facilitate personalised therapy. In this review, we explore different methodologies to derive imaging habitats in glioblastoma, strategies to overcome its technical challenges, contrast experiences to other cancers, and describe potential clinical applications.
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Affiliation(s)
- Mueez Waqar
- Department of Neurosurgery, Geoffrey Jefferson Brain Research Centre, Manchester Centre for Clinical Neurosciences, Northern Care Alliance NHS Foundation Trust, Manchester Academic Health Sciences Centre, Manchester, United Kingdom
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health and Manchester Cancer Research Centre, University of Manchester, Manchester, United Kingdom
| | - Petra J. Van Houdt
- Department of Radiation Oncology, the Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Eline Hessen
- Department of Radiation Oncology, the Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Ka-Loh Li
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health and Manchester Cancer Research Centre, University of Manchester, Manchester, United Kingdom
| | - Xiaoping Zhu
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health and Manchester Cancer Research Centre, University of Manchester, Manchester, United Kingdom
| | - Alan Jackson
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health and Manchester Cancer Research Centre, University of Manchester, Manchester, United Kingdom
- Department of Neuroradiology, Geoffrey Jefferson Brain Research Centre, Manchester Centre for Clinical Neurosciences, Northern Care Alliance NHS Foundation Trust, Manchester Academic Health Sciences Centre, Manchester, United Kingdom
| | - Mudassar Iqbal
- Division of Informatics, Imaging and Data Sciences, Faculty of Biology, Medicine and Health and Manchester Cancer Research Centre, University of Manchester, Manchester, United Kingdom
| | - James O’Connor
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health and Manchester Cancer Research Centre, University of Manchester, Manchester, United Kingdom
- Department of Radiology, The Christie NHS Foundation Trust, Manchester, United Kingdom
| | - Ibrahim Djoukhadar
- Department of Neuroradiology, Geoffrey Jefferson Brain Research Centre, Manchester Centre for Clinical Neurosciences, Northern Care Alliance NHS Foundation Trust, Manchester Academic Health Sciences Centre, Manchester, United Kingdom
| | - Uulke A. van der Heide
- Department of Radiation Oncology, the Netherlands Cancer Institute, Amsterdam, Netherlands
| | - David J. Coope
- Department of Neurosurgery, Geoffrey Jefferson Brain Research Centre, Manchester Centre for Clinical Neurosciences, Northern Care Alliance NHS Foundation Trust, Manchester Academic Health Sciences Centre, Manchester, United Kingdom
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health and Manchester Cancer Research Centre, University of Manchester, Manchester, United Kingdom
| | - Gerben R. Borst
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health and Manchester Cancer Research Centre, University of Manchester, Manchester, United Kingdom
- Department of Clinical Oncology, The Christie NHS Foundation Trust, Manchester, United Kingdom
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8
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Bailo M, Pecco N, Callea M, Scifo P, Gagliardi F, Presotto L, Bettinardi V, Fallanca F, Mapelli P, Gianolli L, Doglioni C, Anzalone N, Picchio M, Mortini P, Falini A, Castellano A. Decoding the Heterogeneity of Malignant Gliomas by PET and MRI for Spatial Habitat Analysis of Hypoxia, Perfusion, and Diffusion Imaging: A Preliminary Study. Front Neurosci 2022; 16:885291. [PMID: 35911979 PMCID: PMC9326318 DOI: 10.3389/fnins.2022.885291] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Accepted: 06/14/2022] [Indexed: 11/13/2022] Open
Abstract
BackgroundTumor heterogeneity poses major clinical challenges in high-grade gliomas (HGGs). Quantitative radiomic analysis with spatial tumor habitat clustering represents an innovative, non-invasive approach to represent and quantify tumor microenvironment heterogeneity. To date, habitat imaging has been applied mainly on conventional magnetic resonance imaging (MRI), although virtually extendible to any imaging modality, including advanced MRI techniques such as perfusion and diffusion MRI as well as positron emission tomography (PET) imaging.ObjectivesThis study aims to evaluate an innovative PET and MRI approach for assessing hypoxia, perfusion, and tissue diffusion in HGGs and derive a combined map for clustering of intra-tumor heterogeneity.Materials and MethodsSeventeen patients harboring HGGs underwent a pre-operative acquisition of MR perfusion (PWI), Diffusion (dMRI) and 18F-labeled fluoroazomycinarabinoside (18F-FAZA) PET imaging to evaluate tumor vascularization, cellularity, and hypoxia, respectively. Tumor volumes were segmented on fluid-attenuated inversion recovery (FLAIR) and T1 post-contrast images, and voxel-wise clustering of each quantitative imaging map identified eight combined PET and physiologic MRI habitats. Habitats’ spatial distribution, quantitative features and histopathological characteristics were analyzed.ResultsA highly reproducible distribution pattern of the clusters was observed among different cases, particularly with respect to morphological landmarks as the necrotic core, contrast-enhancing vital tumor, and peritumoral infiltration and edema, providing valuable supplementary information to conventional imaging. A preliminary analysis, performed on stereotactic bioptic samples where exact intracranial coordinates were available, identified a reliable correlation between the expected microenvironment of the different spatial habitats and the actual histopathological features. A trend toward a higher representation of the most aggressive clusters in WHO (World Health Organization) grade IV compared to WHO III was observed.ConclusionPreliminary findings demonstrated high reproducibility of the PET and MRI hypoxia, perfusion, and tissue diffusion spatial habitat maps and correlation with disease-specific histopathological features.
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Affiliation(s)
- Michele Bailo
- Vita-Salute San Raffaele University, Milan, Italy
- Department of Neurosurgery and Gamma Knife Radiosurgery, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Nicolò Pecco
- Neuroradiology Unit and CERMAC, IRCCS Ospedale San Raffaele, Milan, Italy
| | | | - Paola Scifo
- Department of Nuclear Medicine, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Filippo Gagliardi
- Department of Neurosurgery and Gamma Knife Radiosurgery, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Luca Presotto
- Department of Nuclear Medicine, IRCCS Ospedale San Raffaele, Milan, Italy
| | | | - Federico Fallanca
- Department of Nuclear Medicine, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Paola Mapelli
- Vita-Salute San Raffaele University, Milan, Italy
- Department of Nuclear Medicine, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Luigi Gianolli
- Department of Nuclear Medicine, IRCCS Ospedale San Raffaele, Milan, Italy
| | | | - Nicoletta Anzalone
- Vita-Salute San Raffaele University, Milan, Italy
- Neuroradiology Unit and CERMAC, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Maria Picchio
- Vita-Salute San Raffaele University, Milan, Italy
- Department of Nuclear Medicine, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Pietro Mortini
- Vita-Salute San Raffaele University, Milan, Italy
- Department of Neurosurgery and Gamma Knife Radiosurgery, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Andrea Falini
- Vita-Salute San Raffaele University, Milan, Italy
- Neuroradiology Unit and CERMAC, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Antonella Castellano
- Vita-Salute San Raffaele University, Milan, Italy
- Neuroradiology Unit and CERMAC, IRCCS Ospedale San Raffaele, Milan, Italy
- *Correspondence: Antonella Castellano,
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9
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Le Fèvre C, Sun R, Cebula H, Thiery A, Antoni D, Schott R, Proust F, Constans JM, Noël G. Ellipsoid calculations versus manual tumor delineations for glioblastoma tumor volume evaluation. Sci Rep 2022; 12:10502. [PMID: 35732848 PMCID: PMC9217851 DOI: 10.1038/s41598-022-13739-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Accepted: 05/27/2022] [Indexed: 11/09/2022] Open
Abstract
In glioblastoma, the response to treatment assessment is essentially based on the 2D tumor size evolution but remains disputable. Volumetric approaches were evaluated for a more accurate estimation of tumor size. This study included 57 patients and compared two volume measurement methods to determine the size of different glioblastoma regions of interest: the contrast-enhancing area, the necrotic area, the gross target volume and the volume of the edema area. The two methods, the ellipsoid formula (the calculated method) and the manual delineation (the measured method) showed a high correlation to determine glioblastoma volume and a high agreement to classify patients assessment response to treatment according to RANO criteria. This study revealed that calculated and measured methods could be used in clinical practice to estimate glioblastoma volume size and to evaluate tumor size evolution.
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Affiliation(s)
- Clara Le Fèvre
- Department of Radiotherapy, ICANS, Institut Cancérologie Strasbourg Europe, 17 Rue Albert Calmette, 67200, Strasbourg Cedex, France.
| | - Roger Sun
- Department of Radiotherapy, Institut Gustave Roussy, Paris-Saclay University, Villejuif, France
| | - Hélène Cebula
- Department of Neurosurgery, Hôpital d'Hautepierre, 1, Avenue Molière, 67200, Strasbourg, France
| | - Alicia Thiery
- Department of Public Health, ICANS, Institut Cancérologie Strasbourg Europe, 17 Rue Albert Calmette, 67200, Strasbourg Cedex, France.
| | - Delphine Antoni
- Department of Radiotherapy, ICANS, Institut Cancérologie Strasbourg Europe, 17 Rue Albert Calmette, 67200, Strasbourg Cedex, France
| | - Roland Schott
- Department of Medical Oncology, ICANS, Institut Cancérologie Strasbourg Europe, 17 Rue Albert Calmette, 67200, Strasbourg Cedex, France
| | - François Proust
- Department of Neurosurgery, Hôpital d'Hautepierre, 1, Avenue Molière, 67200, Strasbourg, France
| | - Jean-Marc Constans
- Department of Radiology, Centre Hospitalier Universitaire d' Amiens, 1 Rond-Point du Professeur Christian Cabrol, 80054, Amiens Cedex 1, France
| | - Georges Noël
- Department of Radiotherapy, ICANS, Institut Cancérologie Strasbourg Europe, 17 Rue Albert Calmette, 67200, Strasbourg Cedex, France
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10
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Fuster-Garcia E, Thokle Hovden I, Fløgstad Svensson S, Larsson C, Vardal J, Bjørnerud A, Emblem KE. Quantification of Tissue Compression Identifies High-Grade Glioma Patients with Reduced Survival. Cancers (Basel) 2022; 14:cancers14071725. [PMID: 35406497 PMCID: PMC8997138 DOI: 10.3390/cancers14071725] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Revised: 03/22/2022] [Accepted: 03/25/2022] [Indexed: 02/01/2023] Open
Abstract
The compression of peritumoral healthy tissue in brain tumor patients is considered a major cause of the life-threatening neurologic symptoms. Although significant deformations caused by the tumor growth can be observed radiologically, the quantification of minor tissue deformations have not been widely investigated. In this study, we propose a method to quantify subtle peritumoral deformations. A total of 127 MRI longitudinal studies from 23 patients with high-grade glioma were included. We estimate longitudinal displacement fields based on a symmetric normalization algorithm and we propose four biomarkers. We assess the interpatient and intrapatient association between proposed biomarkers and the survival based on Cox analyses, and the potential of the biomarkers to stratify patients according to their survival based on Kaplan−Meier analysis. Biomarkers show a significant intrapatient association with survival (p < 0.05); however, only compression biomarkers show the ability to stratify patients between those with higher and lower overall survival (AUC = 0.83, HR = 6.30, p < 0.05 for CompCH). The compression biomarkers present three times higher Hazard Ratios than those representing only displacement. Our study provides a robust and automated method for quantifying and delineating compression in the peritumoral area. Based on the proposed methodology, we found an association between lower compression in the peritumoral area and good prognosis in high-grade glial tumors.
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Affiliation(s)
- Elies Fuster-Garcia
- Biomedical Data Science Laboratory, Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de València, 46022 Valencia, Spain
- Correspondence:
| | - Ivar Thokle Hovden
- Department of Diagnostic Physics, Oslo University Hospital, 0372 Oslo, Norway; (I.T.H.); (S.F.S.); (K.E.E.)
- Department of Physics, University of Oslo, 0316 Oslo, Norway;
| | - Siri Fløgstad Svensson
- Department of Diagnostic Physics, Oslo University Hospital, 0372 Oslo, Norway; (I.T.H.); (S.F.S.); (K.E.E.)
- Department of Physics, University of Oslo, 0316 Oslo, Norway;
| | - Christopher Larsson
- Department of Neurosurgery, Oslo University Hospital, 0372 Oslo, Norway;
- Unit for Computational Radiology and Artificial Intelligence, Oslo University Hospital, 0372 Oslo, Norway;
| | - Jonas Vardal
- Unit for Computational Radiology and Artificial Intelligence, Oslo University Hospital, 0372 Oslo, Norway;
- Department of Radiology, Drammen Hospital, Vestre Viken Hospital Trust, 3004 Drammen, Norway
| | - Atle Bjørnerud
- Department of Physics, University of Oslo, 0316 Oslo, Norway;
- Unit for Computational Radiology and Artificial Intelligence, Oslo University Hospital, 0372 Oslo, Norway;
- Department of Psychology, Faculty for Social Sciences, University of Oslo, 0851 Oslo, Norway
| | - Kyrre E. Emblem
- Department of Diagnostic Physics, Oslo University Hospital, 0372 Oslo, Norway; (I.T.H.); (S.F.S.); (K.E.E.)
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11
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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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12
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Álvarez-Torres MDM, Fuster-García E, Juan-Albarracín J, Reynés G, Aparici-Robles F, Ferrer-Lozano J, García-Gómez JM. Local detection of microvessels in IDH-wildtype glioblastoma using relative cerebral blood volume: an imaging marker useful for astrocytoma grade 4 classification. BMC Cancer 2022; 22:40. [PMID: 34991512 PMCID: PMC8734263 DOI: 10.1186/s12885-021-09117-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 12/15/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The microvessels area (MVA), derived from microvascular proliferation, is a biomarker useful for high-grade glioma classification. Nevertheless, its measurement is costly, labor-intense, and invasive. Finding radiologic correlations with MVA could provide a complementary non-invasive approach without an extra cost and labor intensity and from the first stage. This study aims to correlate imaging markers, such as relative cerebral blood volume (rCBV), and local MVA in IDH-wildtype glioblastoma, and to propose this imaging marker as useful for astrocytoma grade 4 classification. METHODS Data from 73 tissue blocks belonging to 17 IDH-wildtype glioblastomas and 7 blocks from 2 IDH-mutant astrocytomas were compiled from the Ivy GAP database. MRI processing and rCBV quantification were carried out using ONCOhabitats methodology. Histologic and MRI co-registration was done manually with experts' supervision, achieving an accuracy of 88.8% of overlay. Spearman's correlation was used to analyze the association between rCBV and microvessel area. Mann-Whitney test was used to study differences of rCBV between blocks with presence or absence of microvessels in IDH-wildtype glioblastoma, as well as to find differences with IDH-mutant astrocytoma samples. RESULTS Significant positive correlations were found between rCBV and microvessel area in the IDH-wildtype blocks (p < 0.001), as well as significant differences in rCBV were found between blocks with microvascular proliferation and blocks without it (p < 0.0001). In addition, significant differences in rCBV were found between IDH-wildtype glioblastoma and IDH-mutant astrocytoma samples, being 2-2.5 times higher rCBV values in IDH-wildtype glioblastoma samples. CONCLUSIONS The proposed rCBV marker, calculated from diagnostic MRIs, can detect in IDH-wildtype glioblastoma those regions with microvessels from those without it, and it is significantly correlated with local microvessels area. In addition, the proposed rCBV marker can differentiate the IDH mutation status, providing a complementary non-invasive method for high-grade glioma classification.
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Affiliation(s)
| | - Elies Fuster-García
- Oslo University Hospital, Department of Diagnostic Physics, 0424, Oslo, Norway
| | - Javier Juan-Albarracín
- Universitat Politècnica de València, Biomedical Data Science Laboratory, ITACA, 46022, Valencia, Spain
| | - Gaspar Reynés
- Health Research Institute Hospital La Fe, Department of Medical Oncology, Cancer Research Group, 46026, Valencia, Spain
| | - Fernando Aparici-Robles
- Health Research Institute Hospital La Fe, Department of Medical Imaging, 46026, Valencia, Spain
| | - Jaime Ferrer-Lozano
- Health Research Institute Hospital La Fe, Department of Pathology, 46026, Valencia, Spain
| | - Juan Miguel García-Gómez
- Universitat Politècnica de València, Biomedical Data Science Laboratory, ITACA, 46022, Valencia, Spain
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13
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Tillmanns N, Lum AE, Cassinelli G, Merkaj S, Verma T, Zeevi T, Staib L, Subramanian H, Bahar RC, Brim W, Lost J, Jekel L, Brackett A, Payabvash S, Ikuta I, Lin M, Bousabarah K, Johnson MH, Cui J, Malhotra A, Omuro A, Turowski B, Aboian MS. Identifying clinically applicable machine learning algorithms for glioma segmentation: recent advances and discoveries. Neurooncol Adv 2022; 4:vdac093. [PMID: 36071926 PMCID: PMC9446682 DOI: 10.1093/noajnl/vdac093] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
Background While there are innumerable machine learning (ML) research algorithms used for segmentation of gliomas, there is yet to be a US FDA cleared product. The aim of this study is to explore the systemic limitations of research algorithms that have prevented translation from concept to product by a review of the current research literature. Methods We performed a systematic literature review on 4 databases. Of 11 727 articles, 58 articles met the inclusion criteria and were used for data extraction and screening using TRIPOD. Results We found that while many articles were published on ML-based glioma segmentation and report high accuracy results, there were substantial limitations in the methods and results portions of the papers that result in difficulty reproducing the methods and translation into clinical practice. Conclusions In addition, we identified that more than a third of the articles used the same publicly available BRaTS and TCIA datasets and are responsible for the majority of patient data on which ML algorithms were trained, which leads to limited generalizability and potential for overfitting and bias.
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Affiliation(s)
- Niklas Tillmanns
- Brain Tumor Research Group, Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut, USA
- University Dusseldorf, Medical Faculty, Department of Diagnostic and Interventional Radiology, Dusseldorf, Germany
| | - Avery E Lum
- Brain Tumor Research Group, Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut, USA
| | - Gabriel Cassinelli
- Brain Tumor Research Group, Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut, USA
| | - Sara Merkaj
- Brain Tumor Research Group, Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut, USA
| | - Tej Verma
- Brain Tumor Research Group, Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut, USA
| | - Tal Zeevi
- Brain Tumor Research Group, Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut, USA
| | - Lawrence Staib
- Brain Tumor Research Group, Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut, USA
| | - Harry Subramanian
- Brain Tumor Research Group, Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut, USA
| | - Ryan C Bahar
- Brain Tumor Research Group, Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut, USA
| | - Waverly Brim
- Brain Tumor Research Group, Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut, USA
| | - Jan Lost
- Brain Tumor Research Group, Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut, USA
| | - Leon Jekel
- Brain Tumor Research Group, Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut, USA
| | - Alexandria Brackett
- Harvey Cushing/John Hay Whitney Medical Library, Yale University, New Haven, Connecticut, USA
| | - Sam Payabvash
- Brain Tumor Research Group, Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut, USA
| | - Ichiro Ikuta
- Brain Tumor Research Group, Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut, USA
| | - MingDe Lin
- Brain Tumor Research Group, Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut, USA
- Visage Imaging, Inc., San Diego, California, USA
| | | | - Michele H Johnson
- Brain Tumor Research Group, Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut, USA
| | - Jin Cui
- Department of Pathology, Boston Children’s Hospital, Boston, Massachusetts, USA
| | - Ajay Malhotra
- Brain Tumor Research Group, Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut, USA
| | - Antonio Omuro
- Department of Neurology and Yale Cancer Center, Yale School of Medicine, New Haven, Connecticut, USA
| | - Bernd Turowski
- University Dusseldorf, Medical Faculty, Department of Diagnostic and Interventional Radiology, Dusseldorf, Germany
| | - Mariam S Aboian
- Brain Tumor Research Group, Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut, USA
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14
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Decreased tissue stiffness in glioblastoma by MR elastography is associated with increased cerebral blood flow. Eur J Radiol 2021; 147:110136. [PMID: 35007982 DOI: 10.1016/j.ejrad.2021.110136] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Revised: 11/09/2021] [Accepted: 12/27/2021] [Indexed: 12/31/2022]
Abstract
PURPOSE Understanding how mechanical properties relate to functional changes in glioblastomas may help explain different treatment response between patients. The aim of this study was to map differences in biomechanical and functional properties between tumor and healthy tissue, to assess any relationship between them and to study their spatial distribution. METHODS Ten patients with glioblastoma and 17 healthy subjects were scanned using MR Elastography, perfusion and diffusion MRI. Stiffness and viscosity measurements G' and G'', cerebral blood flow (CBF), apparent diffusion coefficient (ADC) and fractional anisotropy (FA) were measured in patients' contrast-enhancing tumor, necrosis, edema, and gray and white matter, and in gray and white matter for healthy subjects. A regression analysis was used to predict CBF as a function of ADC, FA, G' and G''. RESULTS Median G' and G'' in contrast-enhancing tumor were 13% and 37% lower than in normal-appearing white matter (P < 0.01), and 8% and 6% lower in necrosis than in contrast-enhancing tumor, respectively (P < 0.05). Tumors showed both inter-patient and intra-patient heterogeneity. Measurements approached values in normal-appearing tissue when moving outward from the tumor core, but abnormal tissue properties were still present in regions of normal-appearing tissue. Using both a linear and a random-forest model, prediction of CBF was improved by adding MRE measurements to the model (P < 0.01). CONCLUSIONS The inclusion of MRE measurements in statistical models helped predict perfusion, with stiffer tissue associated with lower perfusion values.
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15
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Álvarez-Torres MDM, Fuster-García E, Balaña C, Puig J, García-Gómez JM. Lack of Benefit of Extending Temozolomide Treatment in Patients with High Vascular Glioblastoma with Methylated MGMT. Cancers (Basel) 2021; 13:5420. [PMID: 34771583 PMCID: PMC8582449 DOI: 10.3390/cancers13215420] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 10/25/2021] [Accepted: 10/25/2021] [Indexed: 11/25/2022] Open
Abstract
In this study, we evaluated the benefit on survival of the combination of methylation of O6-methylguanine-DNA methyltransferase (MGMT) promotor gene and moderate vascularity in glioblastoma using a retrospective dataset of 123 patients from a multicenter cohort. MRI processing and calculation of relative cerebral blood volume (rCBV), used to define moderate- and high-vascular groups, were performed with the automatic ONCOhabitats method. We assessed the previously proposed rCBV threshold (10.7) and the new calculated ones (9.1 and 9.8) to analyze the association with survival for different populations according to vascularity and MGMT methylation status. We found that patients included in the moderate-vascular group had longer survival when MGMT is methylated (significant median survival difference of 174 days, p = 0.0129*). However, we did not find significant differences depending on the MGMT methylation status for the high-vascular group (p = 0.9119). In addition, we investigated the combined correlation of MGMT methylation status and rCBV with the prognostic effect of the number of temozolomide cycles, and only significant results were found for the moderate-vascular group. In conclusion, there is a lack of benefit of extending temozolomide treatment for patients with high vascular glioblastomas, even presenting MGMT methylation. Preliminary results suggest that patients with moderate vascularity and methylated MGMT glioblastomas would benefit more from prolonged adjuvant chemotherapy.
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Affiliation(s)
- María del Mar Álvarez-Torres
- Biomedical Data Science Laboratory, Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de València, 46022 Valencia, Spain; (E.F.-G.); (J.M.G.-G.)
| | - Elies Fuster-García
- Biomedical Data Science Laboratory, Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de València, 46022 Valencia, Spain; (E.F.-G.); (J.M.G.-G.)
- Department of Diagnostic Physics, Oslo University Hospital, 0450 Oslo, Norway
| | - Carmen Balaña
- Institut Catala d’Oncologia (ICO), Applied Research Group in Oncology (B-ARGO Group), Institut Investigació Germans Trias i Pujol (IGTP), 08916 Badalona, Spain;
| | - Josep Puig
- Institut de Diagnostic per la Image (IDI), Hospital Dr. Josep Trueta, 17007 Girona, Spain;
| | - Juan M. García-Gómez
- Biomedical Data Science Laboratory, Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de València, 46022 Valencia, Spain; (E.F.-G.); (J.M.G.-G.)
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16
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Keil VC, Gielen GH, Pintea B, Baumgarten P, Datsi A, Hittatiya K, Simon M, Hattingen E. DCE-MRI in Glioma, Infiltration Zone and Healthy Brain to Assess Angiogenesis: A Biopsy Study. Clin Neuroradiol 2021; 31:1049-1058. [PMID: 33900414 PMCID: PMC8648693 DOI: 10.1007/s00062-021-01015-3] [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: 11/09/2020] [Accepted: 03/22/2021] [Indexed: 12/29/2022]
Abstract
Purpose To explore the focal predictability of vascular growth factor expression and neovascularization using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in glioma. Methods 120 brain biopsies were taken in vital tumor, infiltration zone and normal brain tissue of 30 glioma patients: 17 IDH(isocitrate dehydrogenase)-wildtype glioblastoma (GBM), 1 IDH-wildtype astrocytoma °III (together prognostic group 1), 3 IDH-mutated GBM (group 2), 3 anaplastic astrocytomas IDH-mutated (group 3), 4 anaplastic oligodendrogliomas and 2 low-grade oligodendrogliomas (together prognostic group 4). A mixed linear model evaluated the predictabilities of microvessel density (MVD), vascular area ratio (VAR), mean vessel size (MVS), vascular endothelial growth factor and receptors (VEGF-A, VEGFR‑2) and vascular endothelial-protein tyrosine phosphatase (VE-PTP) expression from Tofts model kinetic and model-free curve parameters. Results All kinetic parameters were associated with VEGF‑A (all p < 0.001) expression. Ktrans, kep and ve were associated with VAR (p = 0.006, 0.004 and 0.01, respectively) and MVS (p = 0.0001, 0.02 and 0.003, respectively) but not MVD (p = 0.84, 0.74 and 0.73, respectively). Prognostic groups differed in Ktrans (p = 0.007) and ve (p = 0.004) values measured in the infiltration zone. Despite significant differences of VAR, MVS, VEGF‑A, VEGFR‑2, and VE-PTP in vital tumor tissue and the infiltration zone (p = 0.0001 for all), there was no significant difference between kinetic parameters measured in these zones. Conclusion The DCE-MRI kinetic parameters show correlations with microvascular parameters in vital tissue and also reveal blood-brain barrier abnormalities in the infiltration zones adequate to differentiate glioma prognostic groups. Supplementary Information The online version of this article (10.1007/s00062-021-01015-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Vera C Keil
- Department of Neuroradiology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany. .,Department of Radiology, Amsterdam University Medical Center, location VUmc, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands.
| | - Gerrit H Gielen
- Department of Neuropathology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Bogdan Pintea
- Department of Neurosurgery, University Hospital BG Bergmannsheil, Bürkle-de-la-Camp-Platz 1, 44789, Bochum, Germany.,Department of Neurosurgery, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Peter Baumgarten
- Department of Neurosurgery, University Hospital Frankfurt, Schleusenweg 2-16, 60528, Frankfurt am Main, Germany.,Institute of Neuropathology (Edinger Institute), University Hospital Frankfurt, Schleusenweg 2-16, 60528, Frankfurt am Main, Germany
| | - Angeliki Datsi
- ITZ, Heinrich-Heine-University Düsseldorf, Moorenstraße 5, 40225, Düsseldorf, Germany
| | - Kanishka Hittatiya
- Center for Pathology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Matthias Simon
- Department of Neurosurgery, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany.,Department of Neurosurgery, Ev. Krankenhaus Bielefeld, Haus Gilead I, Burgsteig 13, 33617, Bielefeld, Germany
| | - Elke Hattingen
- Department of Neuroradiology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany.,Department of Neuroradiology, University Hospital Frankfurt, Schleusenweg 2-16, 60528, Frankfurt am Main, Germany
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Digernes I, Nilsen LB, Grøvik E, Bjørnerud A, Løvland G, Vik-Mo E, Meling TR, Saxhaug C, Helland Å, Jacobsen KD, Geier O, Emblem KE. Noise dependency in vascular parameters from combined gradient-echo and spin-echo DSC MRI. Phys Med Biol 2020; 65:225020. [PMID: 33200748 DOI: 10.1088/1361-6560/abb71a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Dynamic susceptibility contrast (DSC) imaging is a widely used technique for assessment of cerebral blood volume (CBV). With combined gradient-echo and spin-echo DSC techniques, measures of the underlying vessel size and vessel architecture can be obtained from the vessel size index (VSI) and vortex area, respectively. However, how noise, and specifically the contrast-to-noise ratio (CNR), affect the estimations of these parameters has largely been overlooked. In order to address this issue, we have performed simulations to generate DSC signals with varying levels of CNR, defined by the peak of relaxation rate curve divided by the standard deviation of the baseline. Moreover, DSC data from 59 brain cancer patients were acquired at two different 3 T-scanners (N = 29 and N = 30, respectively), where CNR and relative parameter maps were obtained. Our simulations showed that the measured parameters were affected by CNR in different ways, where low CNR led to overestimations of CBV and underestimations of VSI and vortex area. In addition, a higher noise-sensitivity was found in vortex area than in CBV and VSI. Results from clinical data were consistent with simulations, and indicated that CNR < 4 gives highly unreliable measurements. Moreover, we have shown that the distribution of values in the tumour regions could change considerably when voxels with CNR below a given cut off are excluded when generating the relative parameter maps. The widespread use of CBV and attractive potential of VSI and vortex area, makes the noise-sensitivity of these parameters found in our study relevant for further use and development of the DSC imaging technique. Our results suggest that the CNR has considerable impact on the measured parameters, with the potential to affect the clinical interpretation of DSC-MRI, and should therefore be taken into account in the clinical decision-making process.
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Affiliation(s)
- Ingrid Digernes
- Department of Diagnostic Physics, Oslo University Hospital, Oslo, Norway. Department of Physics, University of Oslo, Oslo, Norway
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18
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Hovden IT, Geier OM, Digernes I, Fuster-Garcia E, Løvland G, Vik-Mo E, Meling TR, Emblem KE. The impact of EPI-based distortion correction of dynamic susceptibility contrast MRI on cerebral blood volume estimation in patients with glioblastoma. Eur J Radiol 2020; 132:109278. [DOI: 10.1016/j.ejrad.2020.109278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 09/02/2020] [Accepted: 09/07/2020] [Indexed: 11/28/2022]
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19
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Chelebian E, Fuster-Garcia E, Álvarez-Torres MDM, Juan-Albarracín J, García-Gómez JM. Higher vascularity at infiltrated peripheral edema differentiates proneural glioblastoma subtype. PLoS One 2020; 15:e0232500. [PMID: 33052913 PMCID: PMC7556526 DOI: 10.1371/journal.pone.0232500] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2020] [Accepted: 09/29/2020] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND AND PURPOSE Genetic classifications are crucial for understanding the heterogeneity of glioblastoma. Recently, perfusion MRI techniques have demonstrated associations molecular alterations. In this work, we investigated whether perfusion markers within infiltrated peripheral edema were associated with proneural, mesenchymal, classical and neural subtypes. MATERIALS AND METHODS ONCOhabitats open web services were used to obtain the cerebral blood volume at the infiltrated peripheral edema for MRI studies of 50 glioblastoma patients from The Cancer Imaging Archive: TCGA-GBM. ANOVA and Kruskal-Wallis tests were carried out in order to assess the association between vascular features and the Verhaak subtypes. For assessing specific differences, Mann-Whitney U-test was conducted. Finally, the association of overall survival with molecular and vascular features was assessed using univariate and multivariate Cox models. RESULTS ANOVA and Kruskal-Wallis tests for the maximum cerebral blood volume at the infiltrated peripheral edema between the four subclasses yielded false discovery rate corrected p-values of <0.001 and 0.02, respectively. This vascular feature was significantly higher (p = 0.0043) in proneural patients compared to the rest of the subtypes while conducting Mann-Whitney U-test. The multivariate Cox model pointed to redundant information provided by vascular features at the peripheral edema and proneural subtype when analyzing overall survival. CONCLUSIONS Higher relative cerebral blood volume at infiltrated peripheral edema is associated with proneural glioblastoma subtype suggesting underlying vascular behavior related to molecular composition in that area.
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Affiliation(s)
- Eduard Chelebian
- Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de València, València, Spain.,Department of Information Technology, Uppsala University, Uppsala, Sweden
| | | | - María Del Mar Álvarez-Torres
- Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de València, València, Spain
| | - Javier Juan-Albarracín
- Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de València, València, Spain
| | - Juan M García-Gómez
- Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de València, València, Spain
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20
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Fuster-Garcia E, Lorente Estellés D, Álvarez-Torres MDM, Juan-Albarracín J, Chelebian E, Rovira A, Acosta CA, Pineda J, Oleaga L, Mollá-Olmos E, Filice S, Due-Tønnessen P, Meling TR, Emblem KE, García-Gómez JM. MGMT methylation may benefit overall survival in patients with moderately vascularized glioblastomas. Eur Radiol 2020; 31:1738-1747. [PMID: 33001310 PMCID: PMC7880975 DOI: 10.1007/s00330-020-07297-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Revised: 08/05/2020] [Accepted: 09/15/2020] [Indexed: 11/29/2022]
Abstract
Objectives To assess the combined role of tumor vascularity, estimated from perfusion MRI, and MGMT methylation status on overall survival (OS) in patients with glioblastoma. Methods A multicentric international dataset including 96 patients from NCT03439332 clinical study were used to study the prognostic relationships between MGMT and perfusion markers. Relative cerebral blood volume (rCBV) in the most vascularized tumor regions was automatically obtained from preoperative MRIs using ONCOhabitats online analysis service. Cox survival regression models and stratification strategies were conducted to define a subpopulation that is particularly favored by MGMT methylation in terms of OS. Results rCBV distributions did not differ significantly (p > 0.05) in the methylated and the non-methylated subpopulations. In patients with moderately vascularized tumors (rCBV < 10.73), MGMT methylation was a positive predictive factor for OS (HR = 2.73, p = 0.003, AUC = 0.70). In patients with highly vascularized tumors (rCBV > 10.73), however, there was no significant effect of MGMT methylation (HR = 1.72, p = 0.10, AUC = 0.56). Conclusions Our results indicate the existence of complementary prognostic information provided by MGMT methylation and rCBV. Perfusion markers could identify a subpopulation of patients who will benefit the most from MGMT methylation. Not considering this information may lead to bias in the interpretation of clinical studies. Key Points • MRI perfusion provides complementary prognostic information to MGMT methylation. • MGMT methylation improves prognosis in glioblastoma patients with moderate vascular profile. • Failure to consider these relations may lead to bias in the interpretation of clinical studies. Electronic supplementary material The online version of this article (10.1007/s00330-020-07297-4) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Elies Fuster-Garcia
- Department of Diagnostic Physics, Oslo University Hospital, Sognsvannsveien 20, 0372, Oslo, Norway.
| | - David Lorente Estellés
- Medical Oncology Service, Hospital Provinicial de Castellón, Castellón de La Plana, Castellón, Spain
| | - María Del Mar Álvarez-Torres
- Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de València, València, Spain
| | - Javier Juan-Albarracín
- Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de València, València, Spain
| | - Eduard Chelebian
- Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de València, València, Spain
| | - Alex Rovira
- Section of Neuroradiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | | | | | | | | | - Silvano Filice
- Department of Medical Physics, University Hospital of Parma, Parma, Italy
| | | | - Torstein R Meling
- Department of Neurosurgery, Oslo University Hospital, Oslo, Norway.,Department of Neurosurgery, Geneva University Hospitals, Geneva, Switzerland
| | - Kyrre E Emblem
- Department of Diagnostic Physics, Oslo University Hospital, Sognsvannsveien 20, 0372, Oslo, Norway
| | - Juan M García-Gómez
- Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de València, València, Spain
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21
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Yoon HG, Cheon W, Jeong SW, Kim HS, Kim K, Nam H, Han Y, Lim DH. Multi-Parametric Deep Learning Model for Prediction of Overall Survival after Postoperative Concurrent Chemoradiotherapy in Glioblastoma Patients. Cancers (Basel) 2020; 12:cancers12082284. [PMID: 32823939 PMCID: PMC7465791 DOI: 10.3390/cancers12082284] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Revised: 08/07/2020] [Accepted: 08/10/2020] [Indexed: 12/24/2022] Open
Abstract
This study aimed to investigate the performance of a deep learning-based survival-prediction model, which predicts the overall survival (OS) time of glioblastoma patients who have received surgery followed by concurrent chemoradiotherapy (CCRT). The medical records of glioblastoma patients who had received surgery and CCRT between January 2011 and December 2017 were retrospectively reviewed. Based on our inclusion criteria, 118 patients were selected and semi-randomly allocated to training and test datasets (3:1 ratio, respectively). A convolutional neural network–based deep learning model was trained with magnetic resonance imaging (MRI) data and clinical profiles to predict OS. The MRI was reconstructed by using four pulse sequences (22 slices) and nine images were selected based on the longest slice of glioblastoma by a physician for each pulse sequence. The clinical profiles consist of personal, genetic, and treatment factors. The concordance index (C-index) and integrated area under the curve (iAUC) of the time-dependent area-under-the-curve curves of each model were calculated to evaluate the performance of the survival-prediction models. The model that incorporated clinical and radiomic features showed a higher C-index (0.768 (95% confidence interval (CI): 0.759, 0.776)) and iAUC (0.790 (95% CI: 0.783, 0.797)) than the model using clinical features alone (C-index = 0.693 (95% CI: 0.685, 0.701); iAUC = 0.723 (95% CI: 0.716, 0.731)) and the model using radiomic features alone (C-index = 0.590 (95% CI: 0.579, 0.600); iAUC = 0.614 (95% CI: 0.607, 0.621)). These improvements to the C-indexes and iAUCs were validated using the 1000-times bootstrapping method; all were statistically significant (p < 0.001). This study suggests the synergistic benefits of using both clinical and radiomic parameters. Furthermore, it indicates the potential of multi-parametric deep learning models for the survival prediction of glioblastoma patients.
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Affiliation(s)
- Han Gyul Yoon
- Department of Radiation Oncology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea;
| | - Wonjoong Cheon
- Samsung Advanced Institute for Health Science & Technology (SAIHST), Sungkyunkwan University School of Medicine, Seoul 06351, Korea; (W.C.); (S.W.J.)
- Proton Therapy Center, National Cancer Center, Goyang 10408, Korea
| | - Sang Woon Jeong
- Samsung Advanced Institute for Health Science & Technology (SAIHST), Sungkyunkwan University School of Medicine, Seoul 06351, Korea; (W.C.); (S.W.J.)
| | - Hye Seung Kim
- Statistics and Data Center, Research Institute for Future Medicine, Samsung Medical Center, Seoul 06351, Korea; (H.S.K.); (K.K.)
| | - Kyunga Kim
- Statistics and Data Center, Research Institute for Future Medicine, Samsung Medical Center, Seoul 06351, Korea; (H.S.K.); (K.K.)
| | - Heerim Nam
- Department of Radiation Oncology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul 03181, Korea;
| | - Youngyih Han
- Department of Radiation Oncology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea;
- Samsung Advanced Institute for Health Science & Technology (SAIHST), Sungkyunkwan University School of Medicine, Seoul 06351, Korea; (W.C.); (S.W.J.)
- Correspondence: (Y.H.); (D.H.L.); Tel.: +82-2-3410-2612 (D.H.L.)
| | - Do Hoon Lim
- Department of Radiation Oncology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea;
- Correspondence: (Y.H.); (D.H.L.); Tel.: +82-2-3410-2612 (D.H.L.)
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