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Savage WM, Yeary MD, Tang AJ, Sperring CP, Argenziano MG, Adapa AR, Yoh N, Canoll P, Bruce JN. Biomarkers of immunotherapy in glioblastoma. Neurooncol Pract 2024; 11:383-394. [PMID: 39006524 PMCID: PMC11241363 DOI: 10.1093/nop/npae028] [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: 07/16/2024] Open
Abstract
Glioblastoma (GBM) is the most common primary brain cancer, comprising half of all malignant brain tumors. Patients with GBM have a poor prognosis, with a median survival of 14-15 months. Current therapies for GBM, including chemotherapy, radiotherapy, and surgical resection, remain inadequate. Novel therapies are required to extend patient survival. Although immunotherapy has shown promise in other cancers, including melanoma and non-small lung cancer, its efficacy in GBM has been limited to subsets of patients. Identifying biomarkers of immunotherapy response in GBM could help stratify patients, identify new therapeutic targets, and develop more effective treatments. This article reviews existing and emerging biomarkers of clinical response to immunotherapy in GBM. The scope of this review includes immune checkpoint inhibitor and antitumoral vaccination approaches, summarizing the variety of molecular, cellular, and computational methodologies that have been explored in the setting of anti-GBM immunotherapies.
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Affiliation(s)
- William M Savage
- Department of Neurological Surgery, Columbia University Irving Medical Center/NY-Presbyterian Hospital, New York, New York, USA
| | - Mitchell D Yeary
- Department of Neurological Surgery, Columbia University Irving Medical Center/NY-Presbyterian Hospital, New York, New York, USA
| | - Anthony J Tang
- Department of Neurological Surgery, Columbia University Irving Medical Center/NY-Presbyterian Hospital, New York, New York, USA
| | - Colin P Sperring
- Department of Neurological Surgery, Columbia University Irving Medical Center/NY-Presbyterian Hospital, New York, New York, USA
| | - Michael G Argenziano
- Department of Neurological Surgery, Columbia University Irving Medical Center/NY-Presbyterian Hospital, New York, New York, USA
| | - Arjun R Adapa
- Department of Neurological Surgery, Columbia University Irving Medical Center/NY-Presbyterian Hospital, New York, New York, USA
| | - Nina Yoh
- Department of Neurological Surgery, Columbia University Irving Medical Center/NY-Presbyterian Hospital, New York, New York, USA
| | - Peter Canoll
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center/NY-Presbyterian Hospital, New York, New York, USA
- Department of Neurological Surgery, Columbia University Irving Medical Center/NY-Presbyterian Hospital, New York, New York, USA
| | - Jeffrey N Bruce
- Department of Neurological Surgery, Columbia University Irving Medical Center/NY-Presbyterian Hospital, New York, New York, USA
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Librizzi G, Lombardi G, Bertoldo A, Manara R. Perioperative imaging predictors of tumor progression and pseudoprogression: A systematic review. Crit Rev Oncol Hematol 2024; 202:104445. [PMID: 38992848 DOI: 10.1016/j.critrevonc.2024.104445] [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: 02/01/2024] [Revised: 06/26/2024] [Accepted: 07/06/2024] [Indexed: 07/13/2024] Open
Abstract
In high-grade gliomas, pseudoprogression after radiation treatment might dramatically impact patient's management. We searched for perioperative imaging predictors of pseudoprogression in high-grade gliomas according to PRISMA guidelines, using MEDLINE/Pubmed and Embase (until January 2024). Study design, sample size, setting, diagnostic gold standard, imaging modalities and contrasts, and differences among variables or measures of diagnostic accuracy were recorded. Study quality was assessed through the QUADAS-2 tool. Twelve studies (11 with MRI, one with PET; 1058 patients) were reviewed. Most studies used a retrospective design (9/12), and structural MRI (7/12). Studies were heterogeneous in metrics and diagnostic reference standards; patient selection bias was a frequent concern. Pseudoprogression and progression showed some significant group differences in perioperative imaging metrics, although often with substantial overlap. Radiomics showed moderate accuracy but requires further validation. Current literature is scarce and limited by methodological concerns, highlighting the need of new predictors and multiparametric approaches.
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Affiliation(s)
- Giovanni Librizzi
- Padova Neuroscience Center (PNC), University of Padova, Padova, Italy; Neuroradiology Unit, Padova University Hospital, Padova, Italy.
| | - Giuseppe Lombardi
- Department of Oncology, Oncology 1, Veneto Institute of Oncology IOV-IRCCS, Padova, Italy.
| | - Alessandra Bertoldo
- Padova Neuroscience Center (PNC), University of Padova, Padova, Italy; Department of Information Engineering, University of Padova, Padova, Italy.
| | - Renzo Manara
- Neuroradiology Unit, Padova University Hospital, Padova, Italy; DIMED, University of Padova, Padova, Italy.
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3
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Ziegenfeuter J, Delbridge C, Bernhardt D, Gempt J, Schmidt-Graf F, Hedderich D, Griessmair M, Thomas M, Meyer HS, Zimmer C, Meyer B, Combs SE, Yakushev I, Metz MC, Wiestler B. Resolving spatial response heterogeneity in glioblastoma. Eur J Nucl Med Mol Imaging 2024:10.1007/s00259-024-06782-y. [PMID: 38837060 DOI: 10.1007/s00259-024-06782-y] [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: 02/28/2024] [Accepted: 05/30/2024] [Indexed: 06/06/2024]
Abstract
PURPOSE Spatial intratumoral heterogeneity poses a significant challenge for accurate response assessment in glioblastoma. Multimodal imaging coupled with advanced image analysis has the potential to unravel this response heterogeneity. METHODS Based on automated tumor segmentation and longitudinal registration with follow-up imaging, we categorized contrast-enhancing voxels of 61 patients with suspected recurrence of glioblastoma into either true tumor progression (TP) or pseudoprogression (PsP). To allow the unbiased analysis of semantically related image regions, adjacent voxels with similar values of cerebral blood volume (CBV), FET-PET, and contrast-enhanced T1w were automatically grouped into supervoxels. We then extracted first-order statistics as well as texture features from each supervoxel. With these features, a Random Forest classifier was trained and validated employing a 10-fold cross-validation scheme. For model evaluation, the area under the receiver operating curve, as well as classification performance metrics were calculated. RESULTS Our image analysis pipeline enabled reliable spatial assessment of tumor response. The predictive model reached an accuracy of 80.0% and a macro-weighted AUC of 0.875, which takes class imbalance into account, in the hold-out samples from cross-validation on supervoxel level. Analysis of feature importances confirmed the significant role of FET-PET-derived features. Accordingly, TP- and PsP-labeled supervoxels differed significantly in their 10th and 90th percentile, as well as the median of tumor-to-background normalized FET-PET. However, CBV- and T1c-related features also relevantly contributed to the model's performance. CONCLUSION Disentangling the intratumoral heterogeneity in glioblastoma holds immense promise for advancing precise local response evaluation and thereby also informing more personalized and localized treatment strategies in the future.
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Affiliation(s)
- Julian Ziegenfeuter
- Department of Neuroradiology, School of Medicine and Health, Technical University of Munich, 81675, München, Germany.
| | - Claire Delbridge
- Department of Pathology, Technical University of Munich, 81675, München, Germany
| | - Denise Bernhardt
- Department of Radiation Oncology, School of Medicine and Health, Technical University of Munich, 81675, München, Germany
| | - Jens Gempt
- Department of Neurosurgery, School of Medicine and Health, Technical University of Munich, 81675, München, Germany
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, 20251, Hamburg, Germany
| | - Friederike Schmidt-Graf
- Department of Neurology, School of Medicine and Health, Technical University of Munich, 81675, München, Germany
| | - Dennis Hedderich
- Department of Neuroradiology, School of Medicine and Health, Technical University of Munich, 81675, München, Germany
| | - Michael Griessmair
- Department of Neuroradiology, School of Medicine and Health, Technical University of Munich, 81675, München, Germany
| | - Marie Thomas
- Department of Neuroradiology, School of Medicine and Health, Technical University of Munich, 81675, München, Germany
| | - Hanno S Meyer
- Department of Neurosurgery, School of Medicine and Health, Technical University of Munich, 81675, München, Germany
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, 20251, Hamburg, Germany
| | - Claus Zimmer
- Department of Neuroradiology, School of Medicine and Health, Technical University of Munich, 81675, München, Germany
| | - Bernhard Meyer
- Department of Neurosurgery, School of Medicine and Health, Technical University of Munich, 81675, München, Germany
| | - Stephanie E Combs
- Department of Radiation Oncology, School of Medicine and Health, Technical University of Munich, 81675, München, Germany
| | - Igor Yakushev
- Department of Nuclear Medicine, School of Medicine and Health, Technical University of Munich, 81675, München, Germany
| | - Marie-Christin Metz
- Department of Neuroradiology, School of Medicine and Health, Technical University of Munich, 81675, München, Germany
| | - Benedikt Wiestler
- Department of Neuroradiology, School of Medicine and Health, Technical University of Munich, 81675, München, Germany
- TranslaTUM, Technical University of Munich, 81675, München, Germany
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Qian X, Tan H, Liu X, Zhao W, Chan MD, Kim P, Zhou X. Radiogenomics-Based Risk Prediction of Glioblastoma Multiforme with Clinical Relevance. Genes (Basel) 2024; 15:718. [PMID: 38927654 PMCID: PMC11202835 DOI: 10.3390/genes15060718] [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: 04/12/2024] [Revised: 05/20/2024] [Accepted: 05/24/2024] [Indexed: 06/28/2024] Open
Abstract
Glioblastoma multiforme (GBM)is the most common and aggressive primary brain tumor. Although temozolomide (TMZ)-based radiochemotherapy improves overall GBM patients' survival, it also increases the frequency of false positive post-treatment magnetic resonance imaging (MRI) assessments for tumor progression. Pseudo-progression (PsP) is a treatment-related reaction with an increased contrast-enhancing lesion size at the tumor site or resection margins miming tumor recurrence on MRI. The accurate and reliable prognostication of GBM progression is urgently needed in the clinical management of GBM patients. Clinical data analysis indicates that the patients with PsP had superior overall and progression-free survival rates. In this study, we aimed to develop a prognostic model to evaluate the tumor progression potential of GBM patients following standard therapies. We applied a dictionary learning scheme to obtain imaging features of GBM patients with PsP or true tumor progression (TTP) from the Wake dataset. Based on these radiographic features, we conducted a radiogenomics analysis to identify the significantly associated genes. These significantly associated genes were used as features to construct a 2YS (2-year survival rate) logistic regression model. GBM patients were classified into low- and high-survival risk groups based on the individual 2YS scores derived from this model. We tested our model using an independent The Cancer Genome Atlas Program (TCGA) dataset and found that 2YS scores were significantly associated with the patient's overall survival. We used two cohorts of the TCGA data to train and test our model. Our results show that the 2YS scores-based classification results from the training and testing TCGA datasets were significantly associated with the overall survival of patients. We also analyzed the survival prediction ability of other clinical factors (gender, age, KPS (Karnofsky performance status), normal cell ratio) and found that these factors were unrelated or weakly correlated with patients' survival. Overall, our studies have demonstrated the effectiveness and robustness of the 2YS model in predicting the clinical outcomes of GBM patients after standard therapies.
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Affiliation(s)
- Xiaohua Qian
- Department of Radiology, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA
- Department of Bioinformatics and Systems Medicine, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA (X.L.); (P.K.)
| | - Hua Tan
- Department of Bioinformatics and Systems Medicine, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA (X.L.); (P.K.)
| | - Xiaona Liu
- Department of Bioinformatics and Systems Medicine, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA (X.L.); (P.K.)
| | - Weiling Zhao
- Department of Bioinformatics and Systems Medicine, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA (X.L.); (P.K.)
| | - Michael D. Chan
- Department of Radiation Oncology, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA
| | - Pora Kim
- Department of Bioinformatics and Systems Medicine, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA (X.L.); (P.K.)
| | - Xiaobo Zhou
- Department of Bioinformatics and Systems Medicine, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA (X.L.); (P.K.)
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Flies CM, Friedrich M, Lohmann P, van Garderen KA, Smits M, Tonn JC, Weller M, Galldiks N, Snijders TJ. Treatment-associated imaging changes in newly diagnosed MGMT promoter-methylated glioblastoma undergoing chemoradiation with or without cilengitide. Neuro Oncol 2024; 26:902-910. [PMID: 38219019 PMCID: PMC11066942 DOI: 10.1093/neuonc/noad247] [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: 07/12/2023] [Indexed: 01/15/2024] Open
Abstract
BACKGROUND Radiological progression may originate from progressive disease (PD) or pseudoprogression/treatment-associated changes. We assessed radiological progression in O6-methylguanine-DNA methyltransferase (MGMT) promoter-methylated glioblastoma treated with standard-of-care chemoradiotherapy with or without the integrin inhibitor cilengitide according to the modified response assessment in neuro-oncology (RANO) criteria of 2017. METHODS Patients with ≥ 3 follow-up MRIs were included. Preliminary PD was defined as a ≥ 25% increase of the sum of products of perpendicular diameters (SPD) of a new or increasing lesion compared to baseline. PD required a second ≥25% increase of the SPD. Treatment-associated changes require stable or regressing disease after preliminary PD. RESULTS Of the 424 evaluable patients, 221 patients (52%) were randomized into the cilengitide and 203 patients (48%) into the control arm. After chemoradiation with or without cilengitide, preliminary PD occurred in 274 patients (65%) during available follow-up, and 88 of these patients (32%) had treatment-associated changes, whereas 67 patients (25%) had PD. The remaining 119 patients (43%) had no further follow-up after preliminary PD. Treatment-associated changes were more common in the cilengitide arm than in the standard-of-care arm (24% vs. 17%; relative risk, 1.3; 95% CI, 1.004-1.795; P = .047). Treatment-associated changes occurred mainly during the first 6 months after RT (54% after 3 months vs. 13% after 6 months). CONCLUSIONS With the modified RANO criteria, the rate of treatment-associated changes was low compared to previous studies in MGMT promoter-methylated glioblastoma. This rate was higher after cilengitide compared to standard-of-care treatment. Confirmatory scans, as recommended in the modified RANO criteria, were not always available reflecting current clinical practice.
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Affiliation(s)
- Christina Maria Flies
- Department of Neurology & Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Michel Friedrich
- Institute of Neuroscience and Medicine (INM-3, INM-4), Research Center Juelich, Juelich, Germany
| | - Philipp Lohmann
- Institute of Neuroscience and Medicine (INM-3, INM-4), Research Center Juelich, Juelich, Germany
| | - Karin Alida van Garderen
- Department of Radiology & Nuclear Medicine, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, The Netherlands
- Brain Tumour Centre, Erasmus MC Cancer Centre, Rotterdam, The Netherlands
- Medical Delta, Delft, The Netherlands
| | - Marion Smits
- Department of Radiology & Nuclear Medicine, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, The Netherlands
- Brain Tumour Centre, Erasmus MC Cancer Centre, Rotterdam, The Netherlands
- Medical Delta, Delft, The Netherlands
| | | | - Michael Weller
- Department of Neurology, Clinical Neuroscience Center, University Hospital and University of Zurich, Zurich, Switzerland
| | - Norbert Galldiks
- Institute of Neuroscience and Medicine (INM-3, INM-4), Research Center Juelich, Juelich, Germany
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- Center for Integrated Oncology (CIO), Universities of Aachen, Bonn, Cologne, and Duesseldorf, Cologne, Germany
| | - Tom Jan Snijders
- Department of Neurology & Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
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Blakstad H, Mendoza Mireles EE, Heggebø LC, Magelssen H, Sprauten M, Johannesen TB, Vik-Mo EO, Leske H, Niehusmann P, Skogen K, Helseth E, Emblem KE, Brandal P. Incidence and outcome of pseudoprogression after radiation therapy in glioblastoma patients: A cohort study. Neurooncol Pract 2024; 11:36-45. [PMID: 38222046 PMCID: PMC10785573 DOI: 10.1093/nop/npad063] [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] [Indexed: 01/16/2024] Open
Abstract
Background Differentiating post-radiation MRI changes from progressive disease (PD) in glioblastoma (GBM) patients represents a major challenge. The clinical problem is two-sided; avoid termination of effective therapy in case of pseudoprogression (PsP) and continuation of ineffective therapy in case of PD. We retrospectively assessed the incidence, management, and prognostic impact of PsP and analyzed factors associated with PsP in a GBM patient cohort. Methods Consecutive GBM patients diagnosed in the South-Eastern Norway Health Region from 2015 to 2018 who had received RT and follow-up MRI were included. Tumor, patient, and treatment characteristics were analyzed in relationship to re-evaluated MRI examinations at 3 and 6 months post-radiation using Response Assessment in Neuro-Oncology criteria. Results A total of 284 patients were included in the study. PsP incidence 3 and 6 months post-radiation was 19.4% and 7.0%, respectively. In adjusted analyses, methylated O6-methylguanine-DNA methyltransferase (MGMT) promoter and the absence of neurological deterioration were associated with PsP at both 3 (p < .001 and p = .029, respectively) and 6 months (p = .045 and p = .034, respectively) post-radiation. For patients retrospectively assessed as PD 3 months post-radiation, there was no survival benefit of treatment change (p = .838). Conclusions PsP incidence was similar to previous reports. In addition to the previously described correlation of methylated MGMT promoter with PsP, we also found that absence of neurological deterioration significantly correlated with PsP. Continuation of temozolomide courses did not seem to compromise survival for patients with PD at 3 months post-radiation; therefore, we recommend continuing adjuvant temozolomide courses in case of inconclusive MRI findings.
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Affiliation(s)
- Hanne Blakstad
- Department of Oncology, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Eduardo Erasmo Mendoza Mireles
- Department of Neurosurgery, Oslo University Hospital, Oslo, Norway
- Vilhelm Magnus Laboratory, Institute for Surgical Research, Oslo University Hospital, Oslo, Norway
| | - Liv Cathrine Heggebø
- Department of Oncology, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | | | - Mette Sprauten
- Department of Oncology, Oslo University Hospital, Oslo, Norway
| | - Tom Børge Johannesen
- Department of Oncology, Oslo University Hospital, Oslo, Norway
- Cancer Registry of Norway, Oslo, Norway
| | - Einar Osland Vik-Mo
- Department of Neurosurgery, Oslo University Hospital, Oslo, Norway
- Vilhelm Magnus Laboratory, Institute for Surgical Research, Oslo University Hospital, Oslo, Norway
| | - Henning Leske
- Department of Pathology, Oslo University Hospital, Oslo
- University of Oslo, Oslo, Norway
| | - Pitt Niehusmann
- Department of Pathology, Oslo University Hospital, Oslo
- Division of Cancer Medicine, Oslo University Hospital, Oslo
| | - Karoline Skogen
- Department of Radiology, Oslo University Hospital, Oslo, Norway
| | - Eirik Helseth
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Neurosurgery, Oslo University Hospital, Oslo, Norway
| | - Kyrre Eeg Emblem
- Department of Physics and Computational Radiology, Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Petter Brandal
- Department of Oncology, Oslo University Hospital, Oslo, Norway
- Institute for Cancer Genetics and Informatics, Oslo University Hospital, Oslo, Norway
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Kossmann MRP, Ehret F, Roohani S, Winter SF, Ghadjar P, Acker G, Senger C, Schmid S, Zips D, Kaul D. Histopathologically confirmed radiation-induced damage of the brain - an in-depth analysis of radiation parameters and spatio-temporal occurrence. Radiat Oncol 2023; 18:198. [PMID: 38087368 PMCID: PMC10717523 DOI: 10.1186/s13014-023-02385-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2023] [Accepted: 11/29/2023] [Indexed: 12/18/2023] Open
Abstract
BACKGROUND Radiation-induced damage (RID) after radiotherapy (RT) of primary brain tumors and metastases can be challenging to clinico-radiographically distinguish from tumor progression. RID includes pseudoprogression and radiation necrosis; the latter being irreversible and often associated with severe symptoms. While histopathology constitutes the diagnostic gold standard, biopsy-controlled clinical studies investigating RID remain limited. Whether certain brain areas are potentially more vulnerable to RID remains an area of active investigation. Here, we analyze histopathologically confirmed cases of RID in relation to the temporal and spatial dose distribution. METHODS Histopathologically confirmed cases of RID after photon-based RT for primary or secondary central nervous system malignancies were included. Demographic, clinical, and dosimetric data were collected from patient records and treatment planning systems. We calculated the equivalent dose in 2 Gy fractions (EQD22) and the biologically effective dose (BED2) for normal brain tissue (α/β ratio of 2 Gy) and analyzed the spatial and temporal distribution using frequency maps. RESULTS Thirty-three patients were identified. High-grade glioma patients (n = 18) mostly received one normofractionated RT series (median cumulative EQD22 60 Gy) to a large planning target volume (PTV) (median 203.9 ccm) before diagnosis of RID. Despite the low EQD22 and BED2, three patients with an accelerated hyperfractionated RT developed RID. In contrast, brain metastases patients (n = 15; 16 RID lesions) were often treated with two or more RT courses and with radiosurgery or fractionated stereotactic RT, resulting in a higher cumulative EQD22 (median 162.4 Gy), to a small PTV (median 6.7 ccm). All (n = 34) RID lesions occurred within the PTV of at least one of the preceding RT courses. RID in the high-grade glioma group showed a frontotemporal distribution pattern, whereas, in metastatic patients, RID was observed throughout the brain with highest density in the parietal lobe. The cumulative EQD22 was significantly lower in RID lesions that involved the subventricular zone (SVZ) than in lesions without SVZ involvement (median 60 Gy vs. 141 Gy, p = 0.01). CONCLUSIONS Accelerated hyperfractionated RT can lead to RID despite computationally low EQD22 and BED2 in high-grade glioma patients. The anatomical location of RID corresponded to the general tumor distribution of gliomas and metastases. The SVZ might be a particularly vulnerable area.
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Affiliation(s)
- Mario R P Kossmann
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiation Oncology, Augustenburger Platz 1, 13353, Berlin, Germany
- Department of Radiotherapy and Radiation Oncology, Pius-Hospital Oldenburg, Georgstr. 12, 26121, Oldenburg, Germany
| | - Felix Ehret
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiation Oncology, Augustenburger Platz 1, 13353, Berlin, Germany
- Charité - Universitätsmedizin Berlin, Berlin, Germany; German Cancer Consortium (DKTK), partner site Berlin, and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Siyer Roohani
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiation Oncology, Augustenburger Platz 1, 13353, Berlin, Germany
- Charité - Universitätsmedizin Berlin, Berlin, Germany; German Cancer Consortium (DKTK), partner site Berlin, and German Cancer Research Center (DKFZ), Heidelberg, Germany
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany
| | - Sebastian F Winter
- Division of Neuro-Oncology, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, USA
| | - Pirus Ghadjar
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiation Oncology, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Güliz Acker
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiation Oncology, Augustenburger Platz 1, 13353, Berlin, Germany
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neurosurgery, Charitéplatz 1, 10117, Berlin, Germany
| | - Carolin Senger
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiation Oncology, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Simone Schmid
- Charité - Universitätsmedizin Berlin, Berlin, Germany; German Cancer Consortium (DKTK), partner site Berlin, and German Cancer Research Center (DKFZ), Heidelberg, Germany
- Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neuropathology, Charitéplatz 1, 10117, Berlin, Germany
| | - Daniel Zips
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiation Oncology, Augustenburger Platz 1, 13353, Berlin, Germany
- Charité - Universitätsmedizin Berlin, Berlin, Germany; German Cancer Consortium (DKTK), partner site Berlin, and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - David Kaul
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiation Oncology, Augustenburger Platz 1, 13353, Berlin, Germany.
- Charité - Universitätsmedizin Berlin, Berlin, Germany; German Cancer Consortium (DKTK), partner site Berlin, and German Cancer Research Center (DKFZ), Heidelberg, Germany.
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8
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Wang W, Tugaoen JD, Fadda P, Toland AE, Ma Q, Elder JB, Giglio P, Otero JJ. Glioblastoma pseudoprogression and true progression reveal spatially variable transcriptional differences. Acta Neuropathol Commun 2023; 11:192. [PMID: 38049893 PMCID: PMC10694987 DOI: 10.1186/s40478-023-01587-w] [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: 04/05/2023] [Accepted: 05/20/2023] [Indexed: 12/06/2023] Open
Abstract
Post-resection radiologic monitoring to identify areas of new or progressive enhancement concerning for cancer recurrence is critical during patients with glioblastoma follow-up. However, treatment-related pseudoprogression presents with similar imaging features but requires different clinical management. While pathologic diagnosis is the gold standard to differentiate true progression and pseudoprogression, the lack of objective clinical standards and admixed histologic presentation creates the needs to (1) validate the accuracy of current approaches and (2) characterize differences between these entities to objectively differentiate true disease. We demonstrated using an online RNAseq repository of recurrent glioblastoma samples that cancer-immune cell activity levels correlate with heterogenous clinical outcomes in patients. Furthermore, nCounter RNA expression analysis of 48 clinical samples taken from second neurosurgical resection supports that pseudoprogression gene expression pathways are dominated with immune activation, whereas progression is predominated with cell cycle activity. Automated image processing and spatial expression analysis however highlight a failure to apply these broad expressional differences in a subset of cases with clinically challenging admixed histology. Encouragingly, applying unsupervised clustering approaches over our segmented histologic images provides novel understanding of morphologically derived differences between progression and pseudoprogression. Spatially derived data further highlighted polarization of myeloid populations that may underscore the tumorgenicity of novel lesions. These findings not only help provide further clarity of potential targets for pathologists to better assist stratification of progression and pseudoprogression, but also highlight the evolution of tumor-immune microenvironment changes which promote tumor recurrence.
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Affiliation(s)
- Wesley Wang
- Department of Pathology, The Ohio State University Wexner Medical Center, The Ohio State University College of Medicine, 4166 Graves Hall, 333 W 10th Avenue, Columbus, OH, 43210, USA
| | - Jonah Domingo Tugaoen
- Department of Pathology, The Ohio State University Wexner Medical Center, The Ohio State University College of Medicine, 4166 Graves Hall, 333 W 10th Avenue, Columbus, OH, 43210, USA
| | - Paolo Fadda
- Genomics Shared Resource-Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA
| | - Amanda Ewart Toland
- Genomics Shared Resource-Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA
- Department of Cancer Biology and Genetics, The Ohio State University, Columbus, OH, USA
| | - Qin Ma
- Department of Biomedical Informatics, The Ohio State University, Columbus, OH, USA
| | - J Brad Elder
- Department of Neurosurgery, The Ohio State University Wexner Medical Center, Columbus, OH, USA
| | - Pierre Giglio
- Department of Neuro-Oncology, The Ohio State University Wexner Medical Center, Columbus, OH, USA
| | - José Javier Otero
- Department of Pathology, The Ohio State University Wexner Medical Center, The Ohio State University College of Medicine, 4166 Graves Hall, 333 W 10th Avenue, Columbus, OH, 43210, USA.
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9
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Pan I, Huang RY. Artificial intelligence in neuroimaging of brain tumors: reality or still promise? Curr Opin Neurol 2023; 36:549-556. [PMID: 37973024 DOI: 10.1097/wco.0000000000001213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2023]
Abstract
PURPOSE OF REVIEW To provide an updated overview of artificial intelligence (AI) applications in neuro-oncologic imaging and discuss current barriers to wider clinical adoption. RECENT FINDINGS A wide variety of AI applications in neuro-oncologic imaging have been developed and researched, spanning tasks from pretreatment brain tumor classification and segmentation, preoperative planning, radiogenomics, prognostication and survival prediction, posttreatment surveillance, and differentiating between pseudoprogression and true disease progression. While earlier studies were largely based on data from a single institution, more recent studies have demonstrated that the performance of these algorithms are also effective on external data from other institutions. Nevertheless, most of these algorithms have yet to see widespread clinical adoption, given the lack of prospective studies demonstrating their efficacy and the logistical difficulties involved in clinical implementation. SUMMARY While there has been significant progress in AI and neuro-oncologic imaging, clinical utility remains to be demonstrated. The next wave of progress in this area will be driven by prospective studies measuring outcomes relevant to clinical practice and go beyond retrospective studies which primarily aim to demonstrate high performance.
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Affiliation(s)
- Ian Pan
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School
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10
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Wen PY, van den Bent M, Youssef G, Cloughesy TF, Ellingson BM, Weller M, Galanis E, Barboriak DP, de Groot J, Gilbert MR, Huang R, Lassman AB, Mehta M, Molinaro AM, Preusser M, Rahman R, Shankar LK, Stupp R, Villanueva-Meyer JE, Wick W, Macdonald DR, Reardon DA, Vogelbaum MA, Chang SM. RANO 2.0: Update to the Response Assessment in Neuro-Oncology Criteria for High- and Low-Grade Gliomas in Adults. J Clin Oncol 2023; 41:5187-5199. [PMID: 37774317 PMCID: PMC10860967 DOI: 10.1200/jco.23.01059] [Citation(s) in RCA: 32] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 07/12/2023] [Accepted: 08/10/2023] [Indexed: 10/01/2023] Open
Abstract
PURPOSE The Response Assessment in Neuro-Oncology (RANO) criteria for high-grade gliomas (RANO-HGG) and low-grade gliomas (RANO-LGG) were developed to improve reliability of response assessment in glioma trials. Over time, some limitations of these criteria were identified, and challenges emerged regarding integrating features of the modified RANO (mRANO) or the immunotherapy RANO (iRANO) criteria. METHODS Informed by data from studies evaluating the different criteria, updates to the RANO criteria are proposed (RANO 2.0). RESULTS We recommend a standard set of criteria for both high- and low-grade gliomas, to be used for all trials regardless of the treatment modalities being evaluated. In the newly diagnosed setting, the postradiotherapy magnetic resonance imaging (MRI), rather than the postsurgical MRI, will be used as the baseline for comparison with subsequent scans. Since the incidence of pseudoprogression is high in the 12 weeks after radiotherapy, continuation of treatment and confirmation of progression during this period with a repeat MRI, or histopathologic evidence of unequivocal recurrent tumor, are required to define tumor progression. However, confirmation scans are not mandatory after this period nor for the evaluation of treatment for recurrent tumors. For treatments with a high likelihood of pseudoprogression, mandatory confirmation of progression with a repeat MRI is highly recommended. The primary measurement remains the maximum cross-sectional area of tumor (two-dimensional) but volumetric measurements are an option. For IDH wild-type glioblastoma, the nonenhancing disease will no longer be evaluated except when assessing response to antiangiogenic agents. In IDH-mutated tumors with a significant nonenhancing component, clinical trials may require evaluating both the enhancing and nonenhancing tumor components for response assessment. CONCLUSION The revised RANO 2.0 criteria refine response assessment in gliomas.
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Affiliation(s)
- Patrick Y. Wen
- Center for Neuro-Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA
| | - Martin van den Bent
- Department Neuro-Oncology, Erasmus MC Cancer Institute, Rotterdam, the Netherlands
| | - Gilbert Youssef
- Center for Neuro-Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA
| | - Timothy F. Cloughesy
- UCLA Brain Tumor Program, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
| | - Benjamin M. Ellingson
- UCLA Brain Tumor Imaging Laboratory, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
| | - Michael Weller
- Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland
| | | | | | - John de Groot
- Division of Neuro-Oncology, Department of Neurosurgery, University of California, San Francisco, CA
| | - Mark R. Gilbert
- Neuro-Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD
| | - Raymond Huang
- Division of Neuro-radiology, Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Andrew B. Lassman
- Division of Neuro-Oncology, Department of Neurology, Herbert Irving Comprehensive Cancer Center and Irving Institute for Clinical and Translational Research, Columbia University Vagelos College of Physicians and Surgeons and New York-Presbyterian Hospital, New York, NY
| | | | - Annette M. Molinaro
- Division of Biomedical Statistics and Informatics, Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA
| | - Matthias Preusser
- Department of Medicine I, Division of Oncology, Medical University of Vienna, Vienna, Austria
| | - Rifaquat Rahman
- Department of Radiation Oncology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Lalitha K. Shankar
- Clinical Trials Branch, Cancer Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, MD
| | - Roger Stupp
- Malnati Brain Tumor Institute, Lurie Comprehensive Cancer Center and Departments of Neurological Surgery, Neurology and Division of Hematology/Oncology, Northwestern University, Chicago, IL
| | | | - Wolfgang Wick
- Department of Neurology Heidelberg University Hospital & Clinical Cooperation Unit Neurooncology, German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - David R. Macdonald
- Departments of Clinical Neurological Sciences and Oncology (Emeritus), Western University, London, Ontario, Canada
| | - David A. Reardon
- Center for Neuro-Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA
| | - Michael A. Vogelbaum
- Departments of Neuro-Oncology and Neurosurgery, Moffitt Cancer Center, Tampa, FL
| | - Susan M. Chang
- Division of Neuro-Oncology, Department of Neurosurgery, University of California, San Francisco, CA
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11
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Zamanian M, Abedi I, Danazadeh F, Amouheidari A, Shahreza BO. Post-chemo-radiotherapy response and pseudo-progression evaluation on glioma cell types by multi-parametric magnetic resonance imaging: a prospective study. BMC Med Imaging 2023; 23:176. [PMID: 37932656 PMCID: PMC10626695 DOI: 10.1186/s12880-023-01135-x] [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: 10/05/2023] [Accepted: 10/20/2023] [Indexed: 11/08/2023] Open
Abstract
BACKGROUND We focused on Differentiated pseudoprogression (PPN) of progression (PN) and the response to radiotherapy (RT) or chemoradiotherapy (CRT) using diffusion and metabolic imaging. METHODS Seventy-five patients with glioma were included in this prospective study (approved by the Iranian Registry of Clinical Trials (IRCT) (IRCT20230904059352N1) in September 2023). Contrast-enhanced lesion volume (CELV), non-enhanced lesion volume (NELV), necrotic tumor volume (NTV), and quantitative values of apparent diffusion coefficient (ADC) and magnetic resonance spectroscopy (Cho/Cr, Cho/NAA and NAA/Cr) were calculated by a neuroradiologist using a semi-automatic method. All patients were followed at one and six months after CRT. RESULTS The results of the study showed statistically significant changes before and six months after RT-CRT for M-CELV in all glioma types (𝑝 < 0.05). In glioma cell types, the changes in M-ADC, M-Cho/Cr, and Cho/NAA indices for PN were incremental and greater for PPN patients. M-NAA/Cr ratio decreased after six months which was significant only on PN for GBM, and Epn (𝑝 < 0.05). A significant difference was observed between diffusion indices, metabolic ratios, and CELV changes after six months in all types (𝑝 < 0.05). None of the patients were suspected PPN one month after treatment. The DWI/ADC indices had higher sensitivity and specificity (98.25% and 96.57%, respectively). CONCLUSION The results of the present study showed that ADC values and Cho/Cr and Cho/NAA ratios can be used to differentiate between patients with PPN and PN, although ADC is more sensitive and specific.
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Affiliation(s)
- Maryam Zamanian
- Department of Medical Physics, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Iraj Abedi
- Department of Medical Physics, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.
| | - Fatemeh Danazadeh
- Department of Radiology, School of Paramedicine, Isfahan University of Medical Sciences, Isfahan, Iran
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Bond KM, Curtin L, Ranjbar S, Afshari AE, Hu LS, Rubin JB, Swanson KR. An image-based modeling framework for predicting spatiotemporal brain cancer biology within individual patients. Front Oncol 2023; 13:1185738. [PMID: 37849813 PMCID: PMC10578440 DOI: 10.3389/fonc.2023.1185738] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Accepted: 08/21/2023] [Indexed: 10/19/2023] Open
Abstract
Imaging is central to the clinical surveillance of brain tumors yet it provides limited insight into a tumor's underlying biology. Machine learning and other mathematical modeling approaches can leverage paired magnetic resonance images and image-localized tissue samples to predict almost any characteristic of a tumor. Image-based modeling takes advantage of the spatial resolution of routine clinical scans and can be applied to measure biological differences within a tumor, changes over time, as well as the variance between patients. This approach is non-invasive and circumvents the intrinsic challenges of inter- and intratumoral heterogeneity that have historically hindered the complete assessment of tumor biology and treatment responsiveness. It can also reveal tumor characteristics that may guide both surgical and medical decision-making in real-time. Here we describe a general framework for the acquisition of image-localized biopsies and the construction of spatiotemporal radiomics models, as well as case examples of how this approach may be used to address clinically relevant questions.
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Affiliation(s)
- Kamila M. Bond
- Mathematical Neuro-Oncology Lab, Department of Neurological Surgery, Mayo Clinic, Phoenix, AZ, United States
- Hospital of University of Pennsylvania, Department of Neurosurgery, Philadelphia, PA, United States
| | - Lee Curtin
- Mathematical Neuro-Oncology Lab, Department of Neurological Surgery, Mayo Clinic, Phoenix, AZ, United States
| | - Sara Ranjbar
- Mathematical Neuro-Oncology Lab, Department of Neurological Surgery, Mayo Clinic, Phoenix, AZ, United States
| | - Ariana E. Afshari
- Mathematical Neuro-Oncology Lab, Department of Neurological Surgery, Mayo Clinic, Phoenix, AZ, United States
| | - Leland S. Hu
- Mathematical Neuro-Oncology Lab, Department of Neurological Surgery, Mayo Clinic, Phoenix, AZ, United States
- Department of Radiology, Mayo Clinic, Phoenix, AZ, United States
| | - Joshua B. Rubin
- Departments of Neuroscience and Pediatrics, Washington University School of Medicine, St. Louis, MO, United States
| | - Kristin R. Swanson
- Mathematical Neuro-Oncology Lab, Department of Neurological Surgery, Mayo Clinic, Phoenix, AZ, United States
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13
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Nierobisch N, Ludovichetti R, Kadali K, Fierstra J, Hüllner M, Michels L, Achangwa NR, Alcaide-Leon P, Weller M, Kulcsar Z, Hainc N. Comparison of clinically available dynamic susceptibility contrast post processing software to differentiate progression from pseudoprogression in post-treatment high grade glioma. Eur J Radiol 2023; 167:111076. [PMID: 37666072 DOI: 10.1016/j.ejrad.2023.111076] [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: 07/04/2023] [Revised: 08/16/2023] [Accepted: 08/30/2023] [Indexed: 09/06/2023]
Abstract
INTRODUCTION The purpose of this retrospective study was to compare two, widely available software packages for calculation of Dynamic Susceptibility Contrast (DSC) perfusion MRI normalized relative Cerebral Blood Volume (rCBV) values to differentiate tumor progression from pseudoprogression in treated high-grade glioma patients. MATERIAL AND METHODS rCBV maps processed by Siemens Syngo.via (Siemens Healthineers) and Olea Sphere (Olea Medical) software packages were co-registered to contrast-enhanced T1 (T1-CE). Regions of interest based on T1-CE were transferred to the rCBV maps. rCBV was calculated using mean values and normalized using contralateral normal- appearing white matter. The Wilcoxon test was performed to assess for significant differences, and software-specific optimal rCBV cutoff values were determined using the Youden index. Interrater reliability was evaluated for two raters using the intraclass correlation coefficient. RESULTS 41 patients (18 females; median age = 59 years; range 21-77 years) with 49 new or size-increasing post-treatment contrast-enhancing lesions were included (tumor progression = 40 lesions; pseudoprogression = 9 lesions). Optimal rCBV cutoffs of 1.31 (Syngo.via) and 2.40 (Olea) were significantly different, with an AUC of 0.74 and 0.78, respectively. Interrater reliability was 0.85. DISCUSSION We demonstrate that different clinically available MRI DSC-perfusion software packages generate significantly different rCBV cutoff values for the differentiation of tumor progression from pseudoprogression in standard-of-care treated high grade gliomas. Physicians may want to determine the unique value of their perfusion software packages on an institutional level in order to maximize diagnostic accuracy when faced with this clinical challenge. Furthermore, combined with implementation of current DSC-perfusion recommendations, multi-center comparability will be improved.
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Affiliation(s)
- Nathalie Nierobisch
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Switzerland
| | - Riccardo Ludovichetti
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Switzerland
| | | | - Jorn Fierstra
- Department of Neurosurgery, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Switzerland
| | - Martin Hüllner
- Department of Nuclear Medicine, University Hospital of Zurich, University of Zurich, Switzerland
| | - Lars Michels
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Switzerland; Neuroscience Center Zurich, University of Zurich and Swiss Federal Institute of Technology Zurich, Zurich, Switzerland
| | - Ngwe Rawlings Achangwa
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Switzerland
| | - Paula Alcaide-Leon
- Department of Medical Imaging, University of Toronto, Toronto, Canada; Joint Department of Medical Imaging, University Health Network, Toronto, Canada
| | - Michael Weller
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Switzerland
| | - Zsolt Kulcsar
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Switzerland
| | - Nicolin Hainc
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Switzerland.
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14
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Zeyen T, Paech D, Weller J, Schäfer N, Tzaridis T, Duffy C, Nitsch L, Schneider M, Potthoff AL, Steinbach JP, Hau P, Schlegel U, Seidel C, Krex D, Grauer O, Goldbrunner R, Zeiner PS, Tabatabai G, Galldiks N, Stummer W, Hattingen E, Glas M, Radbruch A, Herrlinger U, Schaub C. Undetected pseudoprogressions in the CeTeG/NOA-09 trial: hints from postprogression survival and MRI analyses. J Neurooncol 2023; 164:607-616. [PMID: 37728779 PMCID: PMC10589172 DOI: 10.1007/s11060-023-04444-x] [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: 08/07/2023] [Accepted: 09/02/2023] [Indexed: 09/21/2023]
Abstract
PURPOSE In the randomized CeTeG/NOA-09 trial, lomustine/temozolomide (CCNU/TMZ) was superior to TMZ therapy regarding overall survival (OS) in MGMT promotor-methylated glioblastoma. Progression-free survival (PFS) and pseudoprogression rates (about 10%) were similar in both arms. Further evaluating this discrepancy, we analyzed patterns of postprogression survival (PPS) and MRI features at first progression according to modified RANO criteria (mRANO). METHODS We classified the patients of the CeTeG/NOA-09 trial according to long vs. short PPS employing a cut-off of 18 months and compared baseline characteristics and survival times. In patients with available MRIs and confirmed progression, the increase in T1-enhancing, FLAIR hyperintense lesion volume and the change in ADC mean value of contrast-enhancing tumor upon progression were determined. RESULTS Patients with long PPS in the CCNU/TMZ arm had a particularly short PFS (5.6 months). PFS in this subgroup was shorter than in the long PPS subgroup of the TMZ arm (11.1 months, p = 0.01). At mRANO-defined progression, patients of the CCNU/TMZ long PPS subgroup had a significantly higher increase of mean ADC values (p = 0.015) and a tendency to a stronger volumetric increase in T1-enhancement (p = 0.22) as compared to long PPS patients of the TMZ arm. CONCLUSION The combination of survival and MRI analyses identified a subgroup of CCNU/TMZ-treated patients with features that sets them apart from other patients in the trial: short first PFS despite long PPS and significant increase in mean ADC values upon mRANO-defined progression. The observed pattern is compatible with the features commonly observed in pseudoprogression suggesting mRANO-undetected pseudoprogressions in the CCNU/TMZ arm of CeTeG/NOA-09.
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Affiliation(s)
- Thomas Zeyen
- Division of Clinical Neurooncology, Department of Neurology, University Hospital Bonn, Bonn, Germany
| | - Daniel Paech
- Department of Neuroradiology, University Hospital Bonn, Bonn, Germany
| | - Johannes Weller
- Division of Clinical Neurooncology, Department of Neurology, University Hospital Bonn, Bonn, Germany
| | - Niklas Schäfer
- Division of Clinical Neurooncology, Department of Neurology, University Hospital Bonn, Bonn, Germany
| | - Theophilos Tzaridis
- Division of Clinical Neurooncology, Department of Neurology, University Hospital Bonn, Bonn, Germany
| | - Cathrina Duffy
- Division of Clinical Neurooncology, Department of Neurology, University Hospital Bonn, Bonn, Germany
| | - Louisa Nitsch
- Division of Clinical Neurooncology, Department of Neurology, University Hospital Bonn, Bonn, Germany
| | | | | | | | - Peter Hau
- Department of Neurology and Wilhelm Sander NeuroOncology Unit, University Hospital Regensburg, Regensburg, Germany
| | - Uwe Schlegel
- Department of Neurology, Klinik Hirslanden, Zürich, Switzerland
| | - Clemens Seidel
- Department of Radiation Oncology, University of Leipzig, Leipzig, Germany
| | - Dietmar Krex
- Department of Neurosurgery, Technische Universität Dresden, Faculty of Medicine and University Hospital Carl Gustav Carus, Fetscherstrasse 74, 01307, Dresden, Germany
| | - Oliver Grauer
- Department of Neurology, University of Münster, Münster, Germany
| | - Roland Goldbrunner
- Center of Neurosurgery Department of General, Neurosurgery University of Cologne, Cologne, Germany
| | - Pia Susan Zeiner
- Dr. Senckenberg Institute of Neurooncology, University of Frankfurt, Frankfurt, Germany
| | - Ghazaleh Tabatabai
- Department of Neurology and Interdisciplinary Neuro-Oncology, Institute for Clinical Brain Research, University Hospital Tübingen, Eberhard Karls University Tübingen, HertieTübingen, Germany
- Center for Neuro-Oncology, Comprehensive Cancer Center Tübingen-Stuttgart, University Hospital Tübingen, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Norbert Galldiks
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany and Research Center Juelich, Inst. of Neuroscience and Medicine (INM-3), Juelich, Germany
| | - Walter Stummer
- Department of Neurosurgery, University of Münster, Münster, Germany
| | - Elke Hattingen
- Department of Neuroradiology, University Hospital Frankfurt, 60590, Frankfurt Am Main, Germany
| | - Martin Glas
- Division of Clinical Neurooncology, Department of Neurology and Center for Translational Neuro- and Behavioral Sciences (C-TNBS), University Medicine Essen, University Duisburg-Essen, Essen, Germany
- German Cancer Consortium (DKTK), Partner Site University Medicine Essen, Hufelandstr. 55, 45147, Essen, Germany
| | | | - Ulrich Herrlinger
- Division of Clinical Neurooncology, Department of Neurology, University Hospital Bonn, Bonn, Germany
| | - Christina Schaub
- Division of Clinical Neurooncology, Department of Neurology, University Hospital Bonn, Bonn, Germany.
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Veikutis V, Brazdziunas M, Keleras E, Basevicius A, Grib A, Skaudickas D, Lukosevicius S. Diagnostic Approaches to Adult-Type Diffuse Glial Tumors: Comparative Literature and Clinical Practice Study. Curr Oncol 2023; 30:7818-7835. [PMID: 37754483 PMCID: PMC10528153 DOI: 10.3390/curroncol30090568] [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: 04/25/2023] [Revised: 07/27/2023] [Accepted: 08/08/2023] [Indexed: 09/28/2023] Open
Abstract
Gliomas are the most frequent intrinsic central nervous system tumors. The new 2021 WHO Classification of Central Nervous System Tumors brought significant changes into the classification of gliomas, that underline the role of molecular diagnostics, with the adult-type diffuse glial tumors now identified primarily by their biomarkers rather than histology. The status of the isocitrate dehydrogenase (IDH) 1 or 2 describes tumors at their molecular level and together with the presence or absence of 1p/19q codeletion are the most important biomarkers used for the classification of adult-type diffuse glial tumors. In recent years terminology has also changed. IDH-mutant, as previously known, is diagnostically used as astrocytoma and IDH-wildtype is used as glioblastoma. A comprehensive understanding of these tumors not only gives patients a more proper treatment and better prognosis but also highlights new difficulties. MR imaging is of the utmost importance for diagnosing and supervising the response to treatment. By monitoring the tumor on followup exams better results can be achieved. Correlations are seen between tumor diagnostic and clinical manifestation and surgical administration, followup care, oncologic treatment, and outcomes. Minimal resection site use of functional imaging (fMRI) and diffusion tensor imaging (DTI) have become indispensable tools in invasive treatment. Perfusion imaging provides insightful information about the vascularity of the tumor, spectroscopy shows metabolic activity, and nuclear medicine imaging displays tumor metabolism. To accommodate better treatment the differentiation of pseudoprogression, pseudoresponse, or radiation necrosis is needed. In this report, we present a literature review of diagnostics of gliomas, the differences in their imaging features, and our radiology's departments accumulated experience concerning gliomas.
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Affiliation(s)
- Vincentas Veikutis
- Medical Academy, Lithuanian University of Health Sciences, LT50161 Kaunas, Lithuania; (M.B.); (E.K.); (A.B.); (D.S.); (S.L.)
| | - Mindaugas Brazdziunas
- Medical Academy, Lithuanian University of Health Sciences, LT50161 Kaunas, Lithuania; (M.B.); (E.K.); (A.B.); (D.S.); (S.L.)
- Faculty of Medicine, Kaunas University of Applied Sciences, LT44162 Kaunas, Lithuania
| | - Evaldas Keleras
- Medical Academy, Lithuanian University of Health Sciences, LT50161 Kaunas, Lithuania; (M.B.); (E.K.); (A.B.); (D.S.); (S.L.)
| | - Algidas Basevicius
- Medical Academy, Lithuanian University of Health Sciences, LT50161 Kaunas, Lithuania; (M.B.); (E.K.); (A.B.); (D.S.); (S.L.)
| | - Andrei Grib
- Department of Internal Medicine, Nicolae Testemitanu State University of Medicine and Pharmacy, MD2004 Chisinau, Moldova;
| | - Darijus Skaudickas
- Medical Academy, Lithuanian University of Health Sciences, LT50161 Kaunas, Lithuania; (M.B.); (E.K.); (A.B.); (D.S.); (S.L.)
| | - Saulius Lukosevicius
- Medical Academy, Lithuanian University of Health Sciences, LT50161 Kaunas, Lithuania; (M.B.); (E.K.); (A.B.); (D.S.); (S.L.)
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16
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Seyve A, Dehais C, Chinot O, Djelad A, Cohen-Moyal E, Bronnimann C, Gourmelon C, Emery E, Colin P, Boone M, Vauléon E, Langlois O, di Stefano AL, Seizeur R, Ghiringhelli F, D’Hombres A, Feuvret L, Guyotat J, Capelle L, Carpentier C, Garnier L, Honnorat J, Meyronet D, Mokhtari K, Figarella-Branger D, Ducray F. Incidence and characteristics of pseudoprogression in IDH-mutant high-grade gliomas: A POLA network study. Neuro Oncol 2023; 25:495-507. [PMID: 35953421 PMCID: PMC10013645 DOI: 10.1093/neuonc/noac194] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Incidence and characteristics of pseudoprogression in isocitrate dehydrogenase-mutant high-grade gliomas (IDHmt HGG) remain to be specifically described. METHODS We analyzed pseudoprogression characteristics and explored the possibility of pseudoprogression misdiagnosis in IDHmt HGG patients, treated with radiotherapy (RT) (with or without chemotherapy [CT]), included in the French POLA network. Pseudoprogression was analyzed in patients with MRI available for review (reference cohort, n = 200). Pseudoprogression misdiagnosis was estimated in this cohort and in an independent cohort (control cohort, n = 543) based on progression-free survival before and after first progression. RESULTS In the reference cohort, 38 patients (19%) presented a pseudoprogression after a median time of 10.5 months after RT. Pseudoprogression characteristics were similar across IDHmt HGG subtypes. In most patients, it consisted of the appearance of one or several infracentimetric, asymptomatic, contrast-enhanced lesions occurring within 2 years after RT. The only factor associated with pseudoprogression occurrence was adjuvant PCV CT. Among patients considered as having a first true progression, 7 out of 41 (17%) in the reference cohort and 35 out of 203 (17%) in the control cohort were retrospectively suspected to have a misdiagnosed pseudoprogression. Patients with a misdiagnosed pseudoprogression were characterized by a time to event and an outcome similar to that of patients with a pseudoprogression but presented with larger and more symptomatic lesions. CONCLUSION In patients with an IDHmt HGG, pseudoprogression occurs later than in IDH-wildtype glioblastomas and seems not only frequent but also frequently misdiagnosed. Within the first 2 years after RT, the possibility of a pseudoprogression should be carefully considered.
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Affiliation(s)
- Antoine Seyve
- Department of Neuro-Oncology, East Group Hospital, Hospices Civils de Lyon, Lyon, France
| | - Caroline Dehais
- Department of Neurology 2-Mazarin, APHP, University Hospital Pitié Salpêtrière-Charles Foix, Paris, France
| | - Olivier Chinot
- Department of Neuro-Oncology, AP-HM, University Hospital Timone, Marseille, France
| | - Apolline Djelad
- Department of Neurosurgery, University Hospital of Lille, Lille, France
| | - Elisabeth Cohen-Moyal
- Department of Radiotherapy, Claudius Regaud Institut, Cancer University Institut of Toulouse, Oncopole 1, Paul Sabatier University, Toulouse III, Toulouse, France
| | - Charlotte Bronnimann
- Department of Medical Oncology, University Hospital of Bordeaux, Bordeaux, France
| | - Carole Gourmelon
- Department of Medical Oncology, West Cancerology Institut René Gauducheau, Saint-Herblain, France
| | - Evelyne Emery
- Department of Neurosurgery, Caen University Hospital, Caen, France
| | - Philippe Colin
- Department of Radiotherapy, Courlancy Institut of Cancer, Rouen, France
| | - Mathieu Boone
- Medical Oncology Department, Amiens University Hospital, Amiens, France
| | | | - Olivier Langlois
- Department of Neurosurgery, University Hospital of Rouen, Rouen, France
| | | | - Romuald Seizeur
- Neurosurgery Department, Hôpital de la cavale blanche, CHU Brest, Brest, France
| | | | - Anne D’Hombres
- Department of Radiotherapy, South Group Hospital, Hospices Civils de Lyon, Lyon, France
| | - Loic Feuvret
- Department of Radiotherapy, APHP, University Hospital Pitié Salpêtrière-Charles Foix, Paris, France
| | - Jacques Guyotat
- Department of Neurosurgery, East Group Hospital, Hospices Civils de Lyon, Lyon, France
| | - Laurent Capelle
- Department of Neurosurgery, APHP, University Hospital Pitié Salpêtrière-Charles Foix, Paris, France
| | - Catherine Carpentier
- Department of Neurology 2-Mazarin, National Institute of Health and Medical Research (Inserm), CNRS, Brain and Spinal Cord Institute, University Hospital Pitié Salpêtrière-Charles Foix, Sorbonne University, Paris, France
| | - Louis Garnier
- Department of Neuro-Oncology, East Group Hospital, Hospices Civils de Lyon, Lyon, France
| | - Jérôme Honnorat
- Department of Neuro-Oncology, East Group Hospital, Hospices Civils de Lyon, Lyon, France
- SynatAc Team, Institute NeuroMyoGène, MeLis INSERM U1314/CNRS UMR 5284, Université de Lyon, Université Claude Bernard Lyon 1, Lyon, France
| | - David Meyronet
- Pathology Department, East Group Hospital, Hospices Civils de Lyon, Lyon, France
- Centre de recherche en Cancérologie de Lyon, INSERM U1052, CNRS UMR 5286, Cancer Cell Plasticity Department, Transcriptome Diversity in Stem Cells Laboratory, Lyon, France
| | - Karima Mokhtari
- Pathology Department, APHP, University Hospital Pitié Salpêtrière-Charles Foix, Paris, France
| | - Dominique Figarella-Branger
- APHM, CNRS, INP, Inst Neurophysiopathol, CHU Timone, Service d’Anatomie Pathologique et de Neuropathologie, Aix-Marseille University, Marseille, France
| | - François Ducray
- Department of Neuro-Oncology, East Group Hospital, Hospices Civils de Lyon, Lyon, France
- Centre de recherche en Cancérologie de Lyon, INSERM U1052, CNRS UMR 5286, Cancer Cell Plasticity Department, Transcriptome Diversity in Stem Cells Laboratory, Lyon, France
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Alsulami TA, Hyare H, Thomas DL, Golay X. The value of arterial spin labelling (ASL) perfusion MRI in the assessment of post-treatment progression in adult glioma: A systematic review and meta-analysis. Neurooncol Adv 2023; 5:vdad122. [PMID: 37841694 PMCID: PMC10576519 DOI: 10.1093/noajnl/vdad122] [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: 10/17/2023] Open
Abstract
Background The distinction between viable tumor and therapy-induced changes is crucial for the clinical management of patients with gliomas. This study aims to quantitatively assess the efficacy of arterial spin labeling (ASL) biomarkers, including relative cerebral blood flow (rCBF) and absolute cerebral blood flow (CBF), for the discrimination of progressive disease (PD) and treatment-related effects. Methods Eight articles were included in the synthesis after searching the literature systematically. Data have been extracted and a meta-analysis using the random-effect model was subsequently carried out. Diagnostic accuracy assessment was also performed. Results This study revealed that there is a significant difference in perfusion measurements between groups with PD and therapy-induced changes. The rCBF yielded a standardized mean difference (SMD) of 1.25 [95% CI 0.75, 1.75] (p < .00001). The maximum perfusion indices (rCBFmax and CBFmax) both showed equivalent discriminatory ability, with SMD of 1.35 [95% CI 0.78, 1.91] (p < .00001) and 1.56 [95% CI 0.79, 2.33] (p < .0001), respectively. Similarly, accuracy estimates were comparable among ASL-derived metrices. Pooled sensitivities [95% CI] were 0.85 [0.67, 0.94], 0.88 [0.71, 0.96], and 0.93 [0.73, 0.98], and pooled specificities [95% CI] were 0.83 [0.71, 0.91], 0.83 [0.67, 0.92], 0.84 [0.67, 0.93], for rCBF, rCBFmax and CBFmax, respectively. Corresponding HSROC area under curve (AUC) [95% CI] were 0.90 [0.87, 0.92], 0.92 [0.89, 0.94], and 0.93 [0.90, 0.95]. Conclusion These results suggest that ASL quantitative biomarkers, particularly rCBFmax and CBFmax, have the potential to discriminate between glioma progression and therapy-induced changes.
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Affiliation(s)
- Tamadur A Alsulami
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Department of Diagnostic Radiology, Faculty of Applied Medical Sciences, King Abdulaziz University (KAU), Jeddah, Saudi Arabia
| | - Harpreet Hyare
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- University College London Hospitals NHS Foundation Trust, London, UK
| | - David L Thomas
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Xavier Golay
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Lysholm Department of Neuroradiology, The National Hospital for Neurology and Neurosurgery, University College Hospitals NHS Trust, London, UK
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18
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Han RH, Johanns TM, Roberts KF, Tao Y, Luo J, Ye Z, Sun P, Blum J, Lin TH, Song SK, Kim AH. Diffusion basis spectrum imaging as an adjunct to conventional MRI leads to earlier diagnosis of high-grade glioma tumor progression versus treatment effect. Neurooncol Adv 2023; 5:vdad050. [PMID: 37215950 PMCID: PMC10195207 DOI: 10.1093/noajnl/vdad050] [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: 05/24/2023] Open
Abstract
Background Following chemoradiotherapy for high-grade glioma (HGG), it is often challenging to distinguish treatment changes from true tumor progression using conventional MRI. The diffusion basis spectrum imaging (DBSI) hindered fraction is associated with tissue edema or necrosis, which are common treatment-related changes. We hypothesized that DBSI hindered fraction may augment conventional imaging for earlier diagnosis of progression versus treatment effect. Methods Adult patients were prospectively recruited if they had a known histologic diagnosis of HGG and completed standard-of-care chemoradiotherapy. DBSI and conventional MRI data were acquired longitudinally beginning 4 weeks post-radiation. Conventional MRI and DBSI metrics were compared with respect to their ability to diagnose progression versus treatment effect. Results Twelve HGG patients were enrolled between August 2019 and February 2020, and 9 were ultimately analyzed (5 progression, 4 treatment effect). Within new or enlarging contrast-enhancing regions, DBSI hindered fraction was significantly higher in the treatment effect group compared to progression group (P = .0004). Compared to serial conventional MRI alone, inclusion of DBSI would have led to earlier diagnosis of either progression or treatment effect in 6 (66.7%) patients by a median of 7.7 (interquartile range = 0-20.1) weeks. Conclusions In the first longitudinal prospective study of DBSI in adult HGG patients, we found that in new or enlarging contrast-enhancing regions following therapy, DBSI hindered fraction is elevated in cases of treatment effect compared to those with progression. Hindered fraction map may be a valuable adjunct to conventional MRI to distinguish tumor progression from treatment effect.
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Affiliation(s)
- Rowland H Han
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Tanner M Johanns
- Division of Oncology, Department of Medicine, Washington University School of Medicine, St. Louis, Missouri, USA
- The Brain Tumor Center, Siteman Cancer Center, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Kaleigh F Roberts
- Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Yu Tao
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Jingqin Luo
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Zezhong Ye
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Peng Sun
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Jacob Blum
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Tsen-Hsuan Lin
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Sheng-Kwei Song
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Albert H Kim
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis, Missouri, USA
- The Brain Tumor Center, Siteman Cancer Center, Washington University School of Medicine, St. Louis, Missouri, USA
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19
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Roques M, Catalaa I, Raveneau M, Attal J, Siegfried A, Darcourt J, Cognard C, de Champfleur NM, Bonneville F. Assessment of the hypervascularized fraction of glioblastomas using a volume analysis of dynamic susceptibility contrast-enhanced MRI may help to identify pseudoprogression. PLoS One 2022; 17:e0270216. [PMID: 36227862 PMCID: PMC9560146 DOI: 10.1371/journal.pone.0270216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Accepted: 06/07/2022] [Indexed: 11/22/2022] Open
Abstract
PURPOSE Although perfusion magnetic resonance imaging (MRI) is widely used to identify pseudoprogression, this advanced technique lacks clinical reliability. Our aim was to develop a parameter assessing the hypervascularized fraction of glioblastomas based on volume analysis of dynamic susceptibility contrast-enhanced MRI and evaluate its performance in the diagnosis of pseudoprogression. METHODS Patients with primary glioblastoma showing lesion progression on the first follow-up MRI after chemoradiotherapy were enrolled retrospectively. On both initial and first follow-up MRIs, the leakage-corrected cerebral blood volume (CBV) maps were post-processed using the conventional hot-spot method and a volume method, after manual segmentation of the contrast-enhanced delineated lesion. The maximum CBV (rCBVmax) was calculated with both methods. Secondly, the threshold of 2 was applied to the CBV values contained in the entire segmented volume, defining our new parameter: %rCBV>2. The probability of pseudoprogression based on rCBVmax and %rCBV>2 was calculated in logistic regression models and diagnostic performance assessed by receiving operator characteristic curves. RESULTS Out of 25 patients, 11 (44%) were classified with pseudoprogression and 14 (56%) with true progression based on the Response Assessement in Neuro-Oncology criteria. rCBVmax was lower for pseudoprogression (3.4 vs. 7.6; p = 0.033) on early follow-up MRI. %rCBV>2, was lower for pseudoprogression on both initial (57.5% vs. 71.3%; p = 0.033) and early follow-up MRIs (22.1% vs. 51.8%; p = 0.0006). On early follow-up MRI, %rCBV>2 had the largest area under the curve for the diagnosis of pseudoprogression: 0.909 [0.725-0.986]. CONCLUSION The fraction of hypervascularization of glioblastomas as assessed by %rCBV>2 was lower in tumours that subsequently developed pseudoprogression both on the initial and early follow-up MRIs. This fractional parameter may help identify pseudoprogression with greater accuracy than rCBVmax.
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Affiliation(s)
- Margaux Roques
- Department of Neuroradiology, Toulouse Hospital, Toulouse, France
- * E-mail:
| | - Isabelle Catalaa
- Department of Neuroradiology, Toulouse Hospital, Toulouse, France
| | - Magali Raveneau
- Department of Neuroradiology, Toulouse Hospital, Toulouse, France
| | - Justine Attal
- Department of Radiotherapy, IUCT Toulouse (Toulouse University Cancer Institute), Toulouse, France
| | | | - Jean Darcourt
- Department of Neuroradiology, Toulouse Hospital, Toulouse, France
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Dajani S, Hill VB, Kalapurakal JA, Horbinski CM, Nesbit EG, Sachdev S, Yalamanchili A, Thomas TO. Imaging of GBM in the Age of Molecular Markers and MRI Guided Adaptive Radiation Therapy. J Clin Med 2022; 11:jcm11195961. [PMID: 36233828 PMCID: PMC9572863 DOI: 10.3390/jcm11195961] [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: 07/19/2022] [Revised: 09/26/2022] [Accepted: 09/29/2022] [Indexed: 12/03/2022] Open
Abstract
Glioblastoma (GBM) continues to be one of the most lethal malignancies and is almost always fatal. In this review article, the role of radiation therapy, systemic therapy, as well as the molecular basis of classifying GBM is described. Technological advances in the treatment of GBM are outlined as well as the diagnostic imaging characteristics of this tumor. In addition, factors that affect prognosis such as differentiating progression from treatment effect is discussed. The role of MRI guided radiation therapy and how this technology may provide a mechanism to improve the care of patients with this disease are described.
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DEGRO practical guideline for central nervous system radiation necrosis part 1: classification and a multistep approach for diagnosis. Strahlenther Onkol 2022; 198:873-883. [PMID: 36038669 PMCID: PMC9515024 DOI: 10.1007/s00066-022-01994-3] [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: 06/09/2022] [Accepted: 07/19/2022] [Indexed: 10/31/2022]
Abstract
PURPOSE The Working Group for Neuro-Oncology of the German Society for Radiation Oncology in cooperation with members of the Neuro-Oncology Working Group of the German Cancer Society aimed to define a practical guideline for the diagnosis and treatment of radiation-induced necrosis (RN) of the central nervous system (CNS). METHODS Panel members of the DEGRO working group invited experts, participated in a series of conferences, supplemented their clinical experience, performed a literature review, and formulated recommendations for medical treatment of RN including bevacizumab in clinical routine. CONCLUSION Diagnosis and treatment of RN requires multidisciplinary structures of care and defined processes. Diagnosis has to be made on an interdisciplinary level with the joint knowledge of a neuroradiologist, radiation oncologist, neurosurgeon, neuropathologist, and neuro-oncologist. A multistep approach as an opportunity to review as many characteristics as possible to improve diagnostic confidence is recommended. Additional information about radiotherapy (RT) techniques is crucial for the diagnosis of RN. Misdiagnosis of untreated and progressive RN can lead to severe neurological deficits. In this practice guideline, we propose a detailed nomenclature of treatment-related changes and a multistep approach for their diagnosis.
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Zhu M, Li S, Kuang Y, Hill VB, Heimberger AB, Zhai L, Zhai S. Artificial intelligence in the radiomic analysis of glioblastomas: A review, taxonomy, and perspective. Front Oncol 2022; 12:924245. [PMID: 35982952 PMCID: PMC9379255 DOI: 10.3389/fonc.2022.924245] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Accepted: 07/04/2022] [Indexed: 11/17/2022] Open
Abstract
Radiological imaging techniques, including magnetic resonance imaging (MRI) and positron emission tomography (PET), are the standard-of-care non-invasive diagnostic approaches widely applied in neuro-oncology. Unfortunately, accurate interpretation of radiological imaging data is constantly challenged by the indistinguishable radiological image features shared by different pathological changes associated with tumor progression and/or various therapeutic interventions. In recent years, machine learning (ML)-based artificial intelligence (AI) technology has been widely applied in medical image processing and bioinformatics due to its advantages in implicit image feature extraction and integrative data analysis. Despite its recent rapid development, ML technology still faces many hurdles for its broader applications in neuro-oncological radiomic analysis, such as lack of large accessible standardized real patient radiomic brain tumor data of all kinds and reliable predictions on tumor response upon various treatments. Therefore, understanding ML-based AI technologies is critically important to help us address the skyrocketing demands of neuro-oncology clinical deployments. Here, we provide an overview on the latest advancements in ML techniques for brain tumor radiomic analysis, emphasizing proprietary and public dataset preparation and state-of-the-art ML models for brain tumor diagnosis, classifications (e.g., primary and secondary tumors), discriminations between treatment effects (pseudoprogression, radiation necrosis) and true progression, survival prediction, inflammation, and identification of brain tumor biomarkers. We also compare the key features of ML models in the realm of neuroradiology with ML models employed in other medical imaging fields and discuss open research challenges and directions for future work in this nascent precision medicine area.
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Affiliation(s)
- Ming Zhu
- Department of Electrical and Computer Engineering, University of Nevada Las Vegas, Las Vegas, NV, United States
| | - Sijia Li
- Kirk Kerkorian School of Medicine, University of Nevada Las Vegas, Las Vegas, NV, United States
| | - Yu Kuang
- Medical Physics Program, Department of Health Physics, University of Nevada Las Vegas, Las Vegas, NV, United States
| | - Virginia B. Hill
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
| | - Amy B. Heimberger
- Department of Neurological Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
- Malnati Brain Tumor Institute of the Lurie Comprehensive Cancer Center, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
| | - Lijie Zhai
- Department of Neurological Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
- Malnati Brain Tumor Institute of the Lurie Comprehensive Cancer Center, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
- *Correspondence: Lijie Zhai, ; Shengjie Zhai,
| | - Shengjie Zhai
- Department of Electrical and Computer Engineering, University of Nevada Las Vegas, Las Vegas, NV, United States
- *Correspondence: Lijie Zhai, ; Shengjie Zhai,
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23
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Maiter A, Butteriss D, English P, Lewis J, Hassani A, Bhatnagar P. Assessing the diagnostic accuracy and interobserver agreement of MRI perfusion in differentiating disease progression and pseudoprogression following treatment for glioblastoma in a tertiary UK centre. Clin Radiol 2022; 77:e568-e575. [DOI: 10.1016/j.crad.2022.04.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Accepted: 04/12/2022] [Indexed: 11/03/2022]
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Malik DG, Rath TJ, Urcuyo Acevedo JC, Canoll PD, Swanson KR, Boxerman JL, Quarles CC, Schmainda KM, Burns TC, Hu LS. Advanced MRI Protocols to Discriminate Glioma From Treatment Effects: State of the Art and Future Directions. FRONTIERS IN RADIOLOGY 2022; 2:809373. [PMID: 37492687 PMCID: PMC10365126 DOI: 10.3389/fradi.2022.809373] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Accepted: 03/01/2022] [Indexed: 07/27/2023]
Abstract
In the follow-up treatment of high-grade gliomas (HGGs), differentiating true tumor progression from treatment-related effects, such as pseudoprogression and radiation necrosis, presents an ongoing clinical challenge. Conventional MRI with and without intravenous contrast serves as the clinical benchmark for the posttreatment surveillance imaging of HGG. However, many advanced imaging techniques have shown promise in helping better delineate the findings in indeterminate scenarios, as posttreatment effects can often mimic true tumor progression on conventional imaging. These challenges are further confounded by the histologic admixture that can commonly occur between tumor growth and treatment-related effects within the posttreatment bed. This review discusses the current practices in the surveillance imaging of HGG and the role of advanced imaging techniques, including perfusion MRI and metabolic MRI.
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Affiliation(s)
- Dania G. Malik
- Department of Radiology, Mayo Clinic, Phoenix, AZ, United States
| | - Tanya J. Rath
- Department of Radiology, Mayo Clinic, Phoenix, AZ, United States
| | - Javier C. Urcuyo Acevedo
- Mathematical Neurooncology Lab, Precision Neurotherapeutics Innovation Program, Mayo Clinic, Phoenix, AZ, United States
| | - Peter D. Canoll
- Departments of Pathology and Cell Biology, Columbia University, New York, NY, United States
| | - Kristin R. Swanson
- Mathematical Neurooncology Lab, Precision Neurotherapeutics Innovation Program, Mayo Clinic, Phoenix, AZ, United States
| | - Jerrold L. Boxerman
- Department of Diagnostic Imaging, Brown University, Providence, RI, United States
| | - C. Chad Quarles
- Department of Neuroimaging Research & Barrow Neuroimaging Innovation Center, Barrow Neurologic Institute, Phoenix, AZ, United States
| | - Kathleen M. Schmainda
- Department of Biophysics & Radiology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Terry C. Burns
- Departments of Neurologic Surgery and Neuroscience, Mayo Clinic, Rochester, MN, United States
| | - Leland S. Hu
- Department of Radiology, Mayo Clinic, Phoenix, AZ, United States
- Mathematical Neurooncology Lab, Precision Neurotherapeutics Innovation Program, Mayo Clinic, Phoenix, AZ, United States
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Reproducibility of volume analysis of dynamic susceptibility contrast perfusion-weighted imaging in untreated glioblastomas. Neuroradiology 2022; 64:1763-1771. [PMID: 35364709 DOI: 10.1007/s00234-022-02937-6] [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: 11/19/2021] [Accepted: 03/25/2022] [Indexed: 10/18/2022]
Abstract
PURPOSE Despite a high variability, the hotspot method is widely used to calculate the cerebral blood volume (CBV) of glioblastomas on DSC-MRI. Our aim was to investigate inter- and intra-observer reproducibility of parameters calculated with the hotspot or a volume method and that of an original parameter assessing the fraction of pixels in the tumour volume displaying rCBV > 2: %rCBV > 2. METHODS Twenty-seven consecutive patients with untreated glioblastoma (age: 63, women: 11) were retrospectively included. Three observers calculated the maximum tumour CBV value (rCBVmax) normalized with a reference ROI in the contralateral white matter (CBVWM) with (i) the hotspot method and (ii) with a volume method following tumour segmentation on 3D contrast-enhanced T1-WI. From this volume method, %rCBV > 2 was also assessed. After 8-12 weeks, one observer repeated all delineations. Intraclass (ICC) and Lin's (LCC) correlation coefficients were used to determine reproducibility. RESULTS Inter-observer reproducibility of rCBVmax was fair with the hotspot and good with the volume method (ICC = 0.46 vs 0.65, p > 0.05). For CBVWM, it was fair with the hotspot and excellent with the volume method (0.53 vs 0.84, p < 0.05). Reproducibility of one pairwise combination of observers was significantly better for both rCBVmax and CBVWM (LCC = 0.33 vs 0.75; 0.52 vs 0.89, p < 0.05). %rCBV > 2 showed excellent inter- and intra-observer reproducibility (ICC = 0.94 and 0.91). CONCLUSION Calculated in glioblastomas with a volume method, rCBVmax and CBVWM yielded good to excellent reproducibility but only fair with the hotspot method. Overall, the volume analysis offers a highly reproducible parameter, %rCBV > 2, that could be promising during the follow-up of such heterogeneous tumours.
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Yildirim M, Baykara M. Differentiation of progressive disease from pseudoprogression using MRI histogram analysis in patients with treated glioblastoma. Acta Neurol Belg 2022; 122:363-368. [PMID: 33555560 DOI: 10.1007/s13760-021-01607-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Accepted: 01/18/2021] [Indexed: 02/08/2023]
Abstract
PURPOSE Conventional magnetic resonance imaging (MRI) technics are insufficient in the differentiation of tumor progression from post-treatment changes in patients with treated glioblastoma. Previous studies have suggested that histogram analysis is a useful tool in the assessment of treatment response in different cancer types. The aim of the study was to to evaluate the effectiveness of MRI histogram analysis in the differentiation of tumor progression from pseudoprogression in patients with treated glioblastoma. METHODS Forty-six patients with glioblastoma who newly developed enhancing lesions following chemoradiation treatment were included in this retrospective study. Histogram analysis was performed from new enhancing lesions on T1-weighted contrast-enhanced MRI. Histogram analysis findings of patients with progression (23) and pseudoprogression (23) were compared. RESULTS Mean, minimum, median, maximum, standard deviation, variance, entropy, skewness, uniformity values were found to be significantly higher in progressive disease (p < 0.05). A receiver-operating characteristic (ROC) curve analysis was performed for mean value, and area under the curve (AUC) was found as 0.975. When the threshold value was selected as 528.86, two groups could be differentiated with 95.7% sensitivity and 87.0% specificity. CONCLUSION MRI histogram analysis can be used for the differentiation of progressive disease from pseudoprogression.
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Bodensohn R, Forbrig R, Quach S, Reis J, Boulesteix AL, Mansmann U, Hadi I, Fleischmann D, Mücke J, Holzgreve A, Albert N, Ruf V, Dorostkar M, Corradini S, Herms J, Belka C, Thon N, Niyazi M. MRI-based contrast clearance analysis shows high differentiation accuracy between radiation-induced reactions and progressive disease after cranial radiotherapy. ESMO Open 2022; 7:100424. [PMID: 35248822 PMCID: PMC9058918 DOI: 10.1016/j.esmoop.2022.100424] [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: 12/02/2021] [Revised: 01/31/2022] [Accepted: 02/01/2022] [Indexed: 11/26/2022] Open
Abstract
Background Pseudoprogression (PsP) or radiation necrosis (RN) may frequently occur after cranial radiotherapy and show a similar imaging pattern compared with progressive disease (PD). We aimed to evaluate the diagnostic accuracy of magnetic resonance imaging-based contrast clearance analysis (CCA) in this clinical setting. Patients and methods Patients with equivocal imaging findings after cranial radiotherapy were consecutively included into this monocentric prospective study. CCA was carried out by software-based automated subtraction of imaging features in late versus early T1-weighted sequences after contrast agent application. Two experienced neuroradiologists evaluated CCA with respect to PsP/RN and PD being blinded for histological findings. The radiological assessment was compared with the histopathological results, and its accuracy was calculated statistically. Results A total of 33 patients were included; 16 (48.5%) were treated because of a primary brain tumor (BT), and 17 (51.1%) because of a secondary BT. In one patient, CCA was technically infeasible. The accuracy of CCA in predicting the histological result was 0.84 [95% confidence interval (CI) 0.67-0.95; one-sided P = 0.051; n = 32]. Sensitivity and specificity of CCA were 0.93 (95% CI 0.66-1.00) and 0.78 (95% CI 0.52-0.94), respectively. The accuracy in patients with secondary BTs was 0.94 (95% CI 0.71-1.00) and nonsignificantly higher compared with patients with primary BT with an accuracy of 0.73 (95% CI 0.45-0.92), P = 0.16. Conclusions In this study, CCA was a highly accurate, easy, and helpful method for distinguishing PsP or RN from PD after cranial radiotherapy, especially in patients with secondary tumors after radiosurgical treatment. CCA is accurate in distinguishing treatment reactions from true PD. CCA was more accurate for irradiated metastases than primary BTs. CCA is not feasible for lesions with no contrast media uptake.
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El-Abtah ME, Talati P, Fu M, Chun B, Clark P, Peters A, Ranasinghe A, He J, Rapalino O, Batchelor TT, Gilberto Gonzalez R, Curry WT, Dietrich J, Gerstner ER, Ratai EM. Magnetic resonance spectroscopy outperforms perfusion in distinguishing between pseudoprogression and disease progression in patients with glioblastoma. Neurooncol Adv 2022; 4:vdac128. [PMID: 36071927 PMCID: PMC9446677 DOI: 10.1093/noajnl/vdac128] [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] [Indexed: 11/12/2022] Open
Abstract
Abstract
Background
There is a need to establish biomarkers that distinguish between pseudoprogression (PsP) and true tumor progression in patients with glioblastoma (GBM) treated with chemoradiation.
Methods
We analyzed magnetic resonance spectroscopic imaging (MRSI) and dynamic susceptibility contrast (DSC) MR perfusion data in patients with GBM with PsP or disease progression after chemoradiation. MRSI metabolites of interest included intratumoral choline (Cho), myo-inositol (mI), glutamate + glutamine (Glx), lactate (Lac), and creatine on the contralateral hemisphere (c-Cr). Student T-tests and area under the ROC curve analyses were used to detect group differences in metabolic ratios and their ability to predict clinical status, respectively.
Results
28 subjects (63 ± 9 years, 19 men) were evaluated. Subjects with true progression (n = 20) had decreased enhancing region mI/c-Cr (P = .011), a marker for more aggressive tumors, compared to those with PsP, which predicted tumor progression (AUC: 0.84 [0.76, 0.92]). Those with true progression had elevated Lac/Glx (P = .0009), a proxy of the Warburg effect, compared to those with PsP which predicted tumor progression (AUC: 0.84 [0.75, 0.92]). Cho/c-Cr did not distinguish between PsP and true tumor progression. Despite rCBV (AUC: 0.70 [0.60, 0.80]) and rCBF (AUC: 0.75 [0.65, 0.84]) being individually predictive of tumor response, they added no additional predictive value when combined with MRSI metabolic markers.
Conclusions
Incorporating enhancing lesion MRSI measures of mI/c-Cr and Lac/Glx into brain tumor imaging protocols can distinguish between PsP and true progression and inform patient management decisions.
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Affiliation(s)
- Mohamed E El-Abtah
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
| | - Pratik Talati
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
- Department of Neurosurgery, Massachusetts General Hospital , Boston, Massachusetts , USA
| | - Melanie Fu
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
| | - Benjamin Chun
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
| | - Patrick Clark
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
| | - Anna Peters
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
| | - Anthony Ranasinghe
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
| | - Julian He
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
| | - Otto Rapalino
- Department of Radiology, Massachusetts General Hospital , Boston, Massachusetts , USA
- Harvard Medical School , Boston, Massachusetts , USA
| | - Tracy T Batchelor
- Harvard Medical School , Boston, Massachusetts , USA
- Brigham and Women’s Hospital, Neurosciences Center , Boston, Massachusetts , USA
| | - R Gilberto Gonzalez
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
- Department of Radiology, Massachusetts General Hospital , Boston, Massachusetts , USA
- Harvard Medical School , Boston, Massachusetts , USA
| | - William T Curry
- Department of Neurosurgery, Massachusetts General Hospital , Boston, Massachusetts , USA
- Harvard Medical School , Boston, Massachusetts , USA
- Massachusetts General Hospital Cancer Center , Boston, Massachusetts , USA
| | - Jorg Dietrich
- Harvard Medical School , Boston, Massachusetts , USA
- Massachusetts General Hospital Cancer Center , Boston, Massachusetts , USA
| | - Elizabeth R Gerstner
- Harvard Medical School , Boston, Massachusetts , USA
- Massachusetts General Hospital Cancer Center , Boston, Massachusetts , USA
| | - Eva-Maria Ratai
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
- Department of Radiology, Massachusetts General Hospital , Boston, Massachusetts , USA
- Harvard Medical School , Boston, Massachusetts , USA
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Abstract
PURPOSE OF REVIEW This review aims to cover current MRI techniques for assessing treatment response in brain tumors, with a focus on radio-induced lesions. RECENT FINDINGS Pseudoprogression and radionecrosis are common radiological entities after brain tumor irradiation and are difficult to distinguish from real progression, with major consequences on daily patient care. To date, shortcomings of conventional MRI have been largely recognized but morphological sequences are still used in official response assessment criteria. Several complementary advanced techniques have been proposed but none of them have been validated, hampering their clinical use. Among advanced MRI, brain perfusion measures increase diagnostic accuracy, especially when added with spectroscopy and susceptibility-weighted imaging. However, lack of reproducibility, because of several hard-to-control variables, is still a major limitation for their standardization in routine protocols. Amide Proton Transfer is an emerging molecular imaging technique that promises to offer new metrics by indirectly quantifying intracellular mobile proteins and peptide concentration. Preliminary studies suggest that this noncontrast sequence may add key biomarkers in tumor evaluation, especially in posttherapeutic settings. SUMMARY Benefits and pitfalls of conventional and advanced imaging on posttreatment assessment are discussed and the potential added value of APT in this clinicoradiological evolving scenario is introduced.
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Affiliation(s)
- Lucia Nichelli
- Department of Neuroradiology, Sorbonne Université, Assistance Publique-Hôpitaux de Paris, Groupe Hospitalier Pitié-Salpêtrière-Charles Foix
- Sorbonne Université, INSERM, CNRS, Assistance Publique-Hôpitaux de Paris, Institut du Cerveau et de la Moelle épinière, boulevard de l’Hôpital, Paris
| | - Stefano Casagranda
- Department of Research & Innovation, Olea Medical, avenue des Sorbiers, La Ciotat, France
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Parent EE, Johnson DR, Gleason T, Villanueva-Meyer JE. Neuro-Oncology Practice Clinical Debate: FDG PET to differentiate glioblastoma recurrence from treatment-related changes. Neurooncol Pract 2021; 8:518-525. [PMID: 34594566 PMCID: PMC8475205 DOI: 10.1093/nop/npab027] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
The ability to accurately differentiate treatment-related changes (ie, pseudoprogression and radiation necrosis) from recurrent glioma remains a critical diagnostic problem in neuro-oncology. Because these entities are treated differently and have vastly different outcomes, accurate diagnosis is necessary to provide optimal patient care. In current practice, this diagnostic quandary commonly requires either serial imaging or histopathologic tissue confirmation. In this article, experts in the field debate the utility of 2-deoxy-2[18F]fluoro-d-glucose positron emission tomography (FDG PET) as an imaging tool to distinguish tumor recurrence from treatment-related changes in a patient with glioblastoma and progressive contrast enhancement on magnetic resonance (MR) following chemoradiotherapy.
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Affiliation(s)
- Ephraim E Parent
- Department of Radiology, Mayo Clinic, Jacksonville, Florida, USA
| | - Derek R Johnson
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Tyler Gleason
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Javier E Villanueva-Meyer
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
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31
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Neuroimaging in the Era of the Evolving WHO Classification of Brain Tumors, From the AJR Special Series on Cancer Staging. AJR Am J Roentgenol 2021; 217:3-15. [PMID: 33502214 DOI: 10.2214/ajr.20.25246] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
The inclusion of molecular and genetic information with histopathologic information defines the framework for brain tumor classification and grading. This framework is reflected in the major restructuring of the WHO brain tumor classification system in 2016 and in numerous subsequent proposed updates reflecting ongoing developments in understanding the impact of tumor genotype on classification and grading. This incorporation of molecular and genetic features improves tumor diagnosis and prediction of tumor behavior and response to treatment. Neuroimaging is essential for the noninvasive assessment of pretreatment tumor grading and for identification and determination of therapeutic efficacy. Use of conventional neuroimaging and physiologic imaging techniques, such as diffusion- and perfusion-weighted MRI, can increase diagnostic confidence before and after treatment. Although the use of neuroimaging to consistently determine tumor genetics is not yet robust, promising developments are on the horizon. Given the complexity of the brain tumor microenvironment, the development and implementation of a standardized reporting system can aid in conveying to radiologists, referring providers, and patients important information about brain tumor response to treatment. The purpose of this article is to review the current state and role of neuroimaging in this continuously evolving field.
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32
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Werner JM, Weller J, Ceccon G, Schaub C, Tscherpel C, Lohmann P, Bauer EK, Schäfer N, Stoffels G, Baues C, Celik E, Marnitz S, Kabbasch C, Gielen GH, Fink GR, Langen KJ, Herrlinger U, Galldiks N. Diagnosis of Pseudoprogression Following Lomustine-Temozolomide Chemoradiation in Newly Diagnosed Glioblastoma Patients Using FET-PET. Clin Cancer Res 2021; 27:3704-3713. [PMID: 33947699 DOI: 10.1158/1078-0432.ccr-21-0471] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Revised: 03/15/2021] [Accepted: 04/28/2021] [Indexed: 11/16/2022]
Abstract
PURPOSE The CeTeG/NOA-09 phase III trial demonstrated a significant survival benefit of lomustine-temozolomide chemoradiation in patients with newly diagnosed glioblastoma with methylated O6-methylguanine-DNA methyltransferase (MGMT) promoter. Following lomustine-temozolomide chemoradiation, late and prolonged pseudoprogression may occur. We here evaluated the value of amino acid PET using O-(2-[18F]fluoroethyl)-l-tyrosine (FET) for differentiating pseudoprogression from tumor progression. EXPERIMENTAL DESIGN We retrospectively identified patients (i) who were treated off-study according to the CeTeG/NOA-09 protocol, (ii) had equivocal MRI findings after radiotherapy, and (iii) underwent additional FET-PET imaging for diagnostic evaluation (number of scans, 1-3). Maximum and mean tumor-to-brain ratios (TBRmax, TBRmean) and dynamic FET uptake parameters (e.g., time-to-peak) were calculated. In patients with more than one FET-PET scan, relative changes of TBR values were evaluated, that is, an increase or decrease of >10% compared with the reference scan was considered as tumor progression or pseudoprogression. Diagnostic performances were evaluated using ROC curve analyses and Fisher exact test. Diagnoses were confirmed histologically or clinicoradiologically. RESULTS We identified 23 patients with 32 FET-PET scans. Within 5-25 weeks after radiotherapy (median time, 9 weeks), pseudoprogression occurred in 11 patients (48%). The parameter TBRmean calculated from the FET-PET performed 10 ± 7 days after the equivocal MRI showed the highest accuracy (87%) to identify pseudoprogression (threshold, <1.95; P = 0.029). The integration of relative changes of TBRmean further improved the accuracy (91%; P < 0.001). Moreover, the combination of static and dynamic parameters increased the specificity to 100% (P = 0.005). CONCLUSIONS The data suggest that FET-PET parameters are of significant clinical value to diagnose pseudoprogression related to lomustine-temozolomide chemoradiation.
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Affiliation(s)
- Jan-Michael Werner
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.
| | - Johannes Weller
- Division of Clinical Neurooncology, Department of Neurology, University Hospital Bonn, Bonn, Germany
| | - Garry Ceccon
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Christina Schaub
- Division of Clinical Neurooncology, Department of Neurology, University Hospital Bonn, Bonn, Germany
| | - Caroline Tscherpel
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Philipp Lohmann
- Institute of Neuroscience and Medicine (INM-3, -4), Research Center Juelich, Juelich, Germany.,Department of Stereotaxy and Functional Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Elena K Bauer
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Niklas Schäfer
- Division of Clinical Neurooncology, Department of Neurology, University Hospital Bonn, Bonn, Germany
| | - Gabriele Stoffels
- Institute of Neuroscience and Medicine (INM-3, -4), Research Center Juelich, Juelich, Germany
| | - Christian Baues
- Department of Radiation Oncology and Cyberknife Center, Faculty of Medicine and University Hospital Cologne, Cologne, Germany
| | - Eren Celik
- Department of Radiation Oncology and Cyberknife Center, Faculty of Medicine and University Hospital Cologne, Cologne, Germany
| | - Simone Marnitz
- Department of Radiation Oncology and Cyberknife Center, Faculty of Medicine and University Hospital Cologne, Cologne, Germany.,Center for Integrated Oncology (CIO), Universities of Aachen, Bonn, Cologne, and Duesseldorf, Germany
| | - Christoph Kabbasch
- Department of Neuroradiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Gerrit H Gielen
- Institute of Neuropathology, University Hospital Bonn, Bonn, Germany
| | - Gereon R Fink
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.,Institute of Neuroscience and Medicine (INM-3, -4), Research Center Juelich, Juelich, Germany
| | - Karl-Josef Langen
- Institute of Neuroscience and Medicine (INM-3, -4), Research Center Juelich, Juelich, Germany.,Center for Integrated Oncology (CIO), Universities of Aachen, Bonn, Cologne, and Duesseldorf, Germany.,Department of Nuclear Medicine, University Hospital Aachen, Aachen, Germany
| | - Ulrich Herrlinger
- Division of Clinical Neurooncology, Department of Neurology, University Hospital Bonn, Bonn, Germany.,Center for Integrated Oncology (CIO), Universities of Aachen, Bonn, Cologne, and Duesseldorf, Germany
| | - Norbert Galldiks
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.,Institute of Neuroscience and Medicine (INM-3, -4), Research Center Juelich, Juelich, Germany.,Center for Integrated Oncology (CIO), Universities of Aachen, Bonn, Cologne, and Duesseldorf, Germany
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Gao F, Zhao W, Li M, Ren X, Jiang H, Cui Y, Lin S. Role of circulating tumor cell detection in differentiating tumor recurrence from treatment necrosis of brain gliomas. Biosci Trends 2021; 15:107-117. [PMID: 33952802 DOI: 10.5582/bst.2021.01017] [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: 11/05/2022]
Abstract
Differentiating treatment necrosis from tumor recurrence poses a diagnostic conundrum for many clinicians in neuro-oncology. To investigate the potential role of circulating tumor cells (CTCs) detection in differentiating tumor recurrence and treatment necrosis in brain gliomas, we retrospectively analyzed the data of 22 consecutive patients with tumor totally removed and new enhancing mass lesion(s) showed on MRI after initial radiotherapy. The 22 patients were finally classified into tumor recurrence group (n = 10) and treatment necrosis group (n = 12), according to evidence from the clinical course (n = 11) and histological confirmation (n = 11). All 22 patients received CTCs detection, and DSC-MRP and 11C-MET-PET were performed on 20 patients (90.9%) and 17patients (77.3%) respectively. The data of the diagnosis efficacy to differentiate the two lesions by CTC detection, MPR and PET were analyzed by ROC analysis. The mean CTCs counts were significantly higher in the tumor recurrence group (6.10 ± 3.28) compared to the treatment necrosis group (1.08 ± 2.54, p < 0.001). The ROC curve showed that an optimized cell count threshold of 2 had 100% sensitivity and 91.2% specificity with AUC = 0.933 to declare tumor recurrence. The diagnostic efficacy of CTC detection was superior to rCBV of DSC-MRP and rSUVmax in MET-PET. Furthermore, we observed that CTCs detection could have a potential role in predicting tumor recurrence in one patient. Our research results preliminarily showed the potential value of CTC detection in differentiating treatment necrosis from tumor recurrence in brain gliomas, and is worthy of further confirmation with large samples involved.
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Affiliation(s)
- Faliang Gao
- Department of Neurosurgery, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, China; Key Laboratory of Endocrine Gland Diseases of Zhejiang Province, China.,Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Wenyan Zhao
- General Practice Department, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Mingxiao Li
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Xiaohui Ren
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Haihui Jiang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Yong Cui
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Song Lin
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
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Li M, Ren X, Dong G, Wang J, Jiang H, Yang C, Zhao X, Zhu Q, Cui Y, Yu K, Lin S. Distinguishing Pseudoprogression From True Early Progression in Isocitrate Dehydrogenase Wild-Type Glioblastoma by Interrogating Clinical, Radiological, and Molecular Features. Front Oncol 2021; 11:627325. [PMID: 33959496 PMCID: PMC8093388 DOI: 10.3389/fonc.2021.627325] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Accepted: 02/12/2021] [Indexed: 12/03/2022] Open
Abstract
Background: Pseudoprogression (PsP) mimics true early progression (TeP) in conventional imaging, which poses a diagnostic challenge in glioblastoma (GBM) patients who undergo standard concurrent chemoradiation (CCRT). This study aimed to investigate whether perioperative markers could distinguish and predict PsP from TeP in de novo isocitrate dehydrogenase (IDH) wild-type GBM patients. Methods: New or progressive gadolinium-enhancing lesions that emerged within 12 weeks after CCRT were defined as early progression. Lesions that remained stable or spontaneously regressed were classified as PsP, otherwise persistently enlarged as TeP. Clinical, radiological, and molecular information were collected for further analysis. Patients in the early progression subgroup were divided into derivation and validation sets (7:3, according to operation date). Results: Among 234 consecutive cases enrolled in this retrospective study, the incidences of PsP, TeP, and neither patterns of progression (nP) were 26.1% (61/234), 37.6% (88/234), and 36.3% (85/234), respectively. In the early progression subgroup, univariate analysis demonstrated female (OR: 2.161, P = 0.026), gross total removal (GTR) of the tumor (OR: 6.571, P < 001), located in the frontal lobe (OR: 2.561, P = 0.008), non-subventricular zone (SVZ) infringement (OR: 10.937, P < 0.001), and methylated O-6-methylguanine-DNA methyltransferase (MGMT) promoter (mMGMTp) (OR: 9.737, P < 0.001) were correlated with PsP, while GTR, non-SVZ infringement, and mMGMTp were further validated in multivariate analysis. Integrating quantitative MGMTp methylation levels from pyrosequencing, GTR, and non-SVZ infringement showed the best discriminative ability in the random forest model for derivation and validation set (AUC: 0.937, 0.911, respectively). Furthermore, a nomogram could effectively evaluate the importance of those markers in developing PsP (C-index: 0.916) and had a well-fitted calibration curve. Conclusion: Integrating those clinical, radiological, and molecular features provided a novel and robust method to distinguish PsP from TeP, which was crucial for subsequent clinical decision making, clinical trial enrollment, and prognostic assessment. By in-depth interrogation of perioperative markers, clinicians could distinguish PsP from TeP independent from advanced imaging.
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Affiliation(s)
- Mingxiao Li
- Department of Neurosurgery, National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xiaohui Ren
- Department of Neurosurgery, National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Gehong Dong
- Department of Pathology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jincheng Wang
- Department of Radiology, Peking University Cancer Hospital, Beijing, China
| | - Haihui Jiang
- Department of Neurosurgery, National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Chuanwei Yang
- Department of Neurosurgery, National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xuzhe Zhao
- Department of Neurosurgery, National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Qinghui Zhu
- Department of Neurosurgery, National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yong Cui
- Department of Neurosurgery, National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Kefu Yu
- Department of Pharmacy, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Song Lin
- Department of Neurosurgery, National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Brain Tumor, Center of Brain Tumor, Institute for Brain Disorders, Beijing, China
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D'Amore F, Grinberg F, Mauler J, Galldiks N, Blazhenets G, Farrher E, Filss C, Stoffels G, Mottaghy FM, Lohmann P, Shah NJ, Langen KJ. Combined 18F-FET PET and diffusion kurtosis MRI in posttreatment glioblastoma: differentiation of true progression from treatment-related changes. Neurooncol Adv 2021; 3:vdab044. [PMID: 34013207 PMCID: PMC8117449 DOI: 10.1093/noajnl/vdab044] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Background Radiological differentiation of tumor progression (TPR) from treatment-related changes (TRC) in pretreated glioblastoma is crucial. This study aimed to explore the diagnostic value of diffusion kurtosis MRI combined with information derived from O-(2-[18F]-fluoroethyl)-l-tyrosine (18F-FET) PET for the differentiation of TPR from TRC in patients with pretreated glioblastoma. Methods Thirty-two patients with histomolecularly defined and pretreated glioblastoma suspected of having TPR were included in this retrospective study. Twenty-one patients were included in the TPR group, and 11 patients in the TRC group, as assessed by neuropathology or clinicoradiological follow-up. Three-dimensional (3D) regions of interest were generated based on increased 18F-FET uptake using a tumor-to-brain ratio of 1.6. Furthermore, diffusion MRI kurtosis maps were obtained from the same regions of interest using co-registered 18F-FET PET images, and advanced histogram analysis of diffusion kurtosis map parameters was applied to generated 3D regions of interest. Diagnostic accuracy was analyzed by receiver operating characteristic curve analysis and combinations of PET and MRI parameters using multivariate logistic regression. Results Parameters derived from diffusion MRI kurtosis maps show high diagnostic accuracy, up to 88%, for differentiating between TPR and TRC. Logistic regression revealed that the highest diagnostic accuracy of 94% (area under the curve, 0.97; sensitivity, 94%; specificity, 91%) was achieved by combining the maximum tumor-to-brain ratio of 18F-FET uptake and diffusion MRI kurtosis metrics. Conclusions The combined use of 18F-FET PET and MRI diffusion kurtosis maps appears to be a promising approach to improve the differentiation of TPR from TRC in pretreated glioblastoma and warrants further investigation.
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Affiliation(s)
- Francesco D'Amore
- Institute of Neuroscience and Medicine, Research Centre Juelich, Juelich, Germany.,Department of Neuroradiology, Circolo Hospital and Macchi Foundation, Varese, Italy
| | - Farida Grinberg
- Institute of Neuroscience and Medicine, Research Centre Juelich, Juelich, Germany
| | - Jörg Mauler
- Institute of Neuroscience and Medicine, Research Centre Juelich, Juelich, Germany
| | - Norbert Galldiks
- Institute of Neuroscience and Medicine, Research Centre Juelich, Juelich, Germany.,Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.,Center for Integrated Oncology (CIO), Universities of Aachen, Bonn, Cologne and Duesseldorf, Germany
| | - Ganna Blazhenets
- Institute of Neuroscience and Medicine, Research Centre Juelich, Juelich, Germany.,Department of Nuclear Medicine, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Ezequiel Farrher
- Institute of Neuroscience and Medicine, Research Centre Juelich, Juelich, Germany
| | - Christian Filss
- Institute of Neuroscience and Medicine, Research Centre Juelich, Juelich, Germany.,Department of Nuclear Medicine, RWTH Aachen University, Aachen, Germany
| | - Gabriele Stoffels
- Institute of Neuroscience and Medicine, Research Centre Juelich, Juelich, Germany
| | - Felix M Mottaghy
- Center for Integrated Oncology (CIO), Universities of Aachen, Bonn, Cologne and Duesseldorf, Germany.,Department of Nuclear Medicine, RWTH Aachen University, Aachen, Germany.,Department of Radiology and Nuclear Medicine, Maastricht University Medical Center (MUMC+), Maastricht, The Netherlands.,Department of Stereotaxy and Functional Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Philipp Lohmann
- Institute of Neuroscience and Medicine, Research Centre Juelich, Juelich, Germany.,Department of Stereotaxy and Functional Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Nadim Jon Shah
- Institute of Neuroscience and Medicine, Research Centre Juelich, Juelich, Germany.,Department of Neurology, RWTH Aachen University, Aachen, Germany.,JARA-BRAIN-Translational Medicine, Aachen, Germany
| | - Karl-Josef Langen
- Institute of Neuroscience and Medicine, Research Centre Juelich, Juelich, Germany.,Center for Integrated Oncology (CIO), Universities of Aachen, Bonn, Cologne and Duesseldorf, Germany.,Department of Nuclear Medicine, RWTH Aachen University, Aachen, Germany
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36
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Freiburg Neuropathology Case Conference : Contrast-enhancing Brain Lesion 6 Months after Resection and Combined Radiotherapy and Chemotherapy of an Unmethylated but IDH R132H-mutated Glioblastoma Multiforme. Clin Neuroradiol 2021; 31:283-288. [PMID: 33625551 PMCID: PMC7943525 DOI: 10.1007/s00062-021-01006-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/09/2021] [Indexed: 10/28/2022]
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37
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Hadi I, Reitz D, Bodensohn R, Roengvoraphoj O, Lietke S, Niyazi M, Tonn JC, Belka C, Thon N, Nachbichler SB. Radiation necrosis after a combination of external beam radiotherapy and iodine-125 brachytherapy in gliomas. Radiat Oncol 2021; 16:40. [PMID: 33622365 PMCID: PMC7903688 DOI: 10.1186/s13014-021-01762-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Accepted: 02/11/2021] [Indexed: 11/29/2022] Open
Abstract
Purpose Frequency and risk profile of radiation necrosis (RN) in patients with glioma undergoing either upfront stereotactic brachytherapy (SBT) and additional salvage external beam radiotherapy (EBRT) after tumor recurrence or vice versa remains unknown. Methods Patients with glioma treated with low-activity temporary iodine-125 SBT at the University of Munich between 1999 and 2016 who had either additional upfront or salvage EBRT were included. Biologically effective doses (BED) were calculated. RN was diagnosed using stereotactic biopsy and/or metabolic imaging. The rate of RN was estimated with the Kaplan Meier method. Risk factors were obtained from logistic regression models. Results Eighty-six patients (49 male, 37 female, median age 47 years) were included. 38 patients suffered from low-grade and 48 from high-grade glioma. Median follow-up was 15 months after second treatment. Fifty-eight patients received upfront EBRT (median total dose: 60 Gy), and 28 upfront SBT (median reference dose: 54 Gy, median dose rate: 10.0 cGy/h). Median time interval between treatments was 19 months. RN was diagnosed in 8/75 patients. The 1- and 2-year risk of RN was 5.1% and 11.7%, respectively. Tumor volume and irradiation time of SBT, number of implanted seeds, and salvage EBRT were risk factors for RN. Neither of the BED values nor the time interval between both treatments gained prognostic influence. Conclusion The combination of upfront EBRT and salvage SBT or vice versa is feasible for glioma patients. The risk of RN is mainly determined by the treatment volume but not by the interval between therapies.
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Affiliation(s)
- Indrawati Hadi
- Department of Radiation Oncology, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany
| | - Daniel Reitz
- Department of Radiation Oncology, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany
| | - Raphael Bodensohn
- Department of Radiation Oncology, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany
| | - Olarn Roengvoraphoj
- Department of Radiation Oncology, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany
| | - Stefanie Lietke
- Department of Neurosurgery, University Hospital, LMU Munich, Munich, Germany
| | - Maximilian Niyazi
- Department of Radiation Oncology, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.,German Cancer Consortium (DKTK), Munich, Germany
| | - Jörg-Christian Tonn
- Department of Neurosurgery, University Hospital, LMU Munich, Munich, Germany
| | - Claus Belka
- Department of Radiation Oncology, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.,German Cancer Consortium (DKTK), Munich, Germany
| | - Niklas Thon
- Department of Neurosurgery, University Hospital, LMU Munich, Munich, Germany
| | - Silke Birgit Nachbichler
- Department of Radiation Oncology, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.
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Wu J, Li L, Jiang G, Zhan H, Zhu X, Yang W. NCAPG2 facilitates glioblastoma cells' malignancy and xenograft tumor growth via HBO1 activation by phosphorylation. Cell Tissue Res 2021; 383:693-706. [PMID: 32897418 DOI: 10.1007/s00441-020-03281-y] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2019] [Accepted: 08/12/2020] [Indexed: 10/23/2022]
Abstract
NCAPG2 (non-SMC condensin II complex subunit G2), as an important factor in cell mitosis, has been the focus in the study of different cancers. However, the role of NCAPG2 in the malignancy of glioblastoma cells remains unknown. The findings from the present study demonstrated that NCAPG2 was significantly increased in human glioblastoma tissues and was associated with poor clinical outcome. Moreover, NCAPG2 could promote proliferation, migration, and invasion and regulate cell cycle in glioblastoma cells. Investigation of the molecular mechanism indicated that NCAPG2 regulated HBO1 phosphorylation and H4 histone acetylase activation, modulated the activation of Wnt/β-catenin pathway, and the binding of MCM protein to chromatin to exert its role. Furthermore, knockdown of HBO1 was found to reverse the effect of NCAPG2 overexpression on cell proliferation, migration, invasion, and cell cycle. In addition, knockdown of NCAPG2 attenuated glioblastoma tumorigenesis in vivo. Taken together, the findings demonstrated that NCAPG2 facilitates the malignancy of glioblastoma cells and xenograft tumor growth via HBO1 activation by phosphorylation. These results improve our understanding of the mechanism underlying glioblastoma progression and may contribute to the identification of novel biomarkers and therapeutic targets for glioblastoma.
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Affiliation(s)
- Jianheng Wu
- Department of Neurosurgery, the People's Hospital of GaoZhou, Gaozhou, Maoming, 525200, Guangdong Province, China
| | - Linfan Li
- Department of Neurosurgery, the People's Hospital of GaoZhou, Gaozhou, Maoming, 525200, Guangdong Province, China
| | - Guangyuan Jiang
- Department of Neurosurgery, Nanxishan Hospital, Guilin, 541000, Guangxi Zhuang Autonomous Region, China
| | - Hui Zhan
- Department of Neurosurgery, the People's Hospital of GaoZhou, Gaozhou, Maoming, 525200, Guangdong Province, China
| | - Xiumei Zhu
- Department of Pathology, the People's Hospital of GaoZhou, Gaozhou, Maoming, 525200, Guangdong, China
| | - Wujun Yang
- Department of Neurosurgery, The Central Hospital of Enshi Tujia and Miao Autonomous Prefecture(Enshi Clinical College of Wuhan University), Enshi Tujia and Miao Autonomous Prefecture, 445000, Hubei, China.
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Strauss SB, Meng A, Ebani EJ, Chiang GC. Imaging Glioblastoma Posttreatment: Progression, Pseudoprogression, Pseudoresponse, Radiation Necrosis. Neuroimaging Clin N Am 2021; 31:103-120. [PMID: 33220823 DOI: 10.1016/j.nic.2020.09.010] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Radiographic monitoring of posttreatment glioblastoma is important for clinical trials and determining next steps in management. Evaluation for tumor progression is confounded by the presence of treatment-related radiographic changes, making a definitive determination less straight-forward. The purpose of this article was to describe imaging tools available for assessing treatment response in glioblastoma, as well as to highlight the definitions, pathophysiology, and imaging features typical of true progression, pseudoprogression, pseudoresponse, and radiation necrosis.
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Affiliation(s)
- Sara B Strauss
- Department of Radiology, Weill Cornell Medical Center, 525 East 68th Street, Box 141, New York, NY 10065, USA
| | - Alicia Meng
- Department of Radiology, Weill Cornell Medical Center, 525 East 68th Street, Box 141, New York, NY 10065, USA
| | - Edward J Ebani
- Department of Radiology, Weill Cornell Medical Center, 525 East 68th Street, Box 141, New York, NY 10065, USA
| | - Gloria C Chiang
- Department of Radiology, Weill Cornell Medical Center, 525 East 68th Street, Box 141, New York, NY 10065, USA.
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40
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Le Fèvre C, Lhermitte B, Ahle G, Chambrelant I, Cebula H, Antoni D, Keller A, Schott R, Thiery A, Constans JM, Noël G. Pseudoprogression versus true progression in glioblastoma patients: A multiapproach literature review: Part 1 - Molecular, morphological and clinical features. Crit Rev Oncol Hematol 2020; 157:103188. [PMID: 33307200 DOI: 10.1016/j.critrevonc.2020.103188] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Revised: 11/12/2020] [Accepted: 11/23/2020] [Indexed: 01/04/2023] Open
Abstract
With new therapeutic protocols, more patients treated for glioblastoma have experienced a suspicious radiologic image of progression (pseudoprogression) during follow-up. Pseudoprogression should be differentiated from true progression because the disease management is completely different. In the case of pseudoprogression, the follow-up continues, and the patient is considered stable. In the case of true progression, a treatment adjustment is necessary. Presently, a pseudoprogression diagnosis certainly needs to be pathologically confirmed. Some important efforts in the radiological, histopathological, and genomic fields have been made to differentiate pseudoprogression from true progression, and the assessment of response criteria exists but remains limited. The aim of this paper is to highlight clinical and pathological markers to differentiate pseudoprogression from true progression through a literature review.
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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
| | - Benoît Lhermitte
- Département of Pathology, Hautepierre University Hospital, 1, Avenue Molière, 67200, Strasbourg, France
| | - Guido Ahle
- Departement of Neurology, Hôpitaux Civils de Colmar, 39 Avenue de la Liberté, 68024, Colmar, France
| | - Isabelle Chambrelant
- Department of Radiotherapy, ICANS, Institut Cancérologie Strasbourg Europe, 17 Rue Albert Calmette, 67200, Strasbourg Cedex, France
| | - Hélène Cebula
- Departement of Neurosurgery, Hautepierre University Hospital, 1, Avenue Molière, 67200, Strasbourg, France
| | - Delphine Antoni
- Department of Radiotherapy, ICANS, Institut Cancérologie Strasbourg Europe, 17 Rue Albert Calmette, 67200, Strasbourg Cedex, France
| | - Audrey Keller
- Department of Radiotherapy, ICANS, Institut Cancérologie Strasbourg Europe, 17 Rue Albert Calmette, 67200, Strasbourg Cedex, France
| | - Roland Schott
- Departement of Medical Oncology, ICANS, Institut Cancérologie Strasbourg Europe, 17 rue Albert Calmette, 67200, Strasbourg Cedex, France
| | - Alicia Thiery
- Department of Public Health, ICANS, Institut Cancérologie Strasbourg Europe, 17 rue Albert Calmette, 67200, Strasbourg Cedex, France
| | - Jean-Marc Constans
- Department of Radiology, Amiens-Pïcardie University Hospital, 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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Tsakiris C, Siempis T, Alexiou GA, Zikou A, Sioka C, Voulgaris S, Argyropoulou MI. Differentiation Between True Tumor Progression of Glioblastoma and Pseudoprogression Using Diffusion-Weighted Imaging and Perfusion-Weighted Imaging: Systematic Review and Meta-analysis. World Neurosurg 2020; 144:e100-e109. [DOI: 10.1016/j.wneu.2020.07.218] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Revised: 07/28/2020] [Accepted: 07/30/2020] [Indexed: 01/08/2023]
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Booth TC, Luis A, Brazil L, Thompson G, Daniel RA, Shuaib H, Ashkan K, Pandey A. Glioblastoma post-operative imaging in neuro-oncology: current UK practice (GIN CUP study). Eur Radiol 2020; 31:2933-2943. [PMID: 33151394 PMCID: PMC8043861 DOI: 10.1007/s00330-020-07387-3] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Revised: 08/13/2020] [Accepted: 10/07/2020] [Indexed: 12/14/2022]
Abstract
OBJECTIVES MRI remains the preferred imaging investigation for glioblastoma. Appropriate and timely neuroimaging in the follow-up period is considered to be important in making management decisions. There is a paucity of evidence-based information in current UK, European and international guidelines regarding the optimal timing and type of neuroimaging following initial neurosurgical treatment. This study assessed the current imaging practices amongst UK neuro-oncology centres, thus providing baseline data and informing future practice. METHODS The lead neuro-oncologist, neuroradiologist and neurosurgeon from every UK neuro-oncology centre were invited to complete an online survey. Participants were asked about current and ideal imaging practices following initial treatment. RESULTS Ninety-two participants from all 31 neuro-oncology centres completed the survey (100% response rate). Most centres routinely performed an early post-operative MRI (87%, 27/31), whereas only a third performed a pre-radiotherapy MRI (32%, 10/31). The number and timing of scans routinely performed during adjuvant TMZ treatment varied widely between centres. At the end of the adjuvant period, most centres performed an MRI (71%, 22/31), followed by monitoring scans at 3 monthly intervals (81%, 25/31). Additional short-interval imaging was carried out in cases of possible pseudoprogression in most centres (71%, 22/31). Routine use of advanced imaging was infrequent; however, the addition of advanced sequences was the most popular suggestion for ideal imaging practice, followed by changes in the timing of EPMRI. CONCLUSION Variations in neuroimaging practices exist after initial glioblastoma treatment within the UK. Multicentre, longitudinal, prospective trials are needed to define the optimal imaging schedule for assessment. KEY POINTS • Variations in imaging practices exist in the frequency, timing and type of interval neuroimaging after initial treatment of glioblastoma within the UK. • Large, multicentre, longitudinal, prospective trials are needed to define the optimal imaging schedule for assessment.
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Affiliation(s)
- Thomas C Booth
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK. .,Department of Neuroradiology Ruskin Wing, King's College Hospital NHS Foundation Trust, London, SE5 9RS, UK.
| | - Aysha Luis
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK.,Department of Neuroradiology, National Hospital For Neurology and Neurosrgery, London, WC1N 3BG, UK
| | - Lucy Brazil
- Department of Oncology, Guy's and St Thomas' NHS Foundation Trust, London, SE1 7EH, UK
| | - Gerry Thompson
- Centre for Clinical Brain Sciences, Edinburgh, EH16 4SB, UK
| | - Rachel A Daniel
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
| | - Haris Shuaib
- Department of Medical Physics, Guy's & St. Thomas' NHS Foundation Trust, London, SE1 7EH, UK.,Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK
| | - Keyoumars Ashkan
- Department of Neurosurgery, King's College Hospital NHS Foundation Trust, London, SE5 9RS, UK
| | - Anmol Pandey
- Faculty of Life Sciences and Medicine, King's College London Strand, London, WC2R 2LS, UK
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Park JE, Kim HS, Kim N, Park SY, Kim YH, Kim JH. Spatiotemporal Heterogeneity in Multiparametric Physiologic MRI Is Associated with Patient Outcomes in IDH-Wildtype Glioblastoma. Clin Cancer Res 2020; 27:237-245. [PMID: 33028594 DOI: 10.1158/1078-0432.ccr-20-2156] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Revised: 08/19/2020] [Accepted: 10/02/2020] [Indexed: 11/16/2022]
Abstract
PURPOSE Heterogeneity in glioblastomas is associated with poorer outcomes, and physiologic heterogeneity can be quantified with noninvasive imaging. We developed spatial habitats based on multiparametric physiologic MRI and evaluated associations between temporal changes in these habitats and progression-free survival (PFS) after concurrent chemoradiotherapy (CCRT) in patients with glioblastoma. EXPERIMENTAL DESIGN Ninety-seven patients with isocitrate dehydrogenase (IDH)-wildtype glioblastoma were enrolled and two serial MRI examinations after CCRT were analyzed. Cerebral blood volumes and apparent diffusion coefficients were grouped using k-means clustering into three spatial habitats. Associations between temporal changes in spatial habitats and PFS were investigated using Cox proportional hazard modeling. The performance of significant predictors for PFS and overall survival (OS) was measured using a discrete increase of habitat (habitat risk score) in a temporal validation set from a prospective registry (n = 53, ClinicalTrials.gov NCT02619890). The site of progression was matched with the spatiotemporal habitats. RESULTS Three spatial habitats of hypervascular cellular, hypovascular cellular, and nonviable tissue were identified. A short-term increase in the hypervascular cellular habitat (HR, 40.0; P = 0.001) and hypovascular cellular habitat was significantly associated with shorter PFS (HR, 3.78; P < 0.001) after CCRT. Combined with clinical predictors, the habitat risk score showed a C-index of 0.79 for PFS and 0.74 for OS and stratified patients with short, intermediate, and long PFS (P = 0.016). An increase in the hypovascular cellular habitat predicted tumor progression sites. CONCLUSIONS Hypovascular cellular habitats derived from multiparametric physiologic MRIs may be useful predictors of clinical outcomes in patients with posttreatment glioblastoma.
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Affiliation(s)
- Ji Eun Park
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Ho Sung Kim
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.
| | | | - Seo Young Park
- Department of Clinical Epidemiology and Biostatistics, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Young-Hoon Kim
- Department of Neurosurgery, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Jeong Hoon Kim
- Department of Neurosurgery, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
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44
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Barajas RF, Schwartz D, McConnell HL, Kersch CN, Li X, Hamilton BE, Starkey J, Pettersson DR, Nickerson JP, Pollock JM, Fu RF, Horvath A, Szidonya L, Varallyay CG, Jaboin JJ, Raslan AM, Dogan A, Cetas JS, Ciporen J, Han SJ, Ambady P, Muldoon LL, Woltjer R, Rooney WD, Neuwelt EA. Distinguishing Extravascular from Intravascular Ferumoxytol Pools within the Brain: Proof of Concept in Patients with Treated Glioblastoma. AJNR Am J Neuroradiol 2020; 41:1193-1200. [PMID: 32527840 DOI: 10.3174/ajnr.a6600] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2019] [Accepted: 04/02/2020] [Indexed: 12/11/2022]
Abstract
BACKGROUND AND PURPOSE Glioblastoma-associated macrophages are a major constituent of the immune response to therapy and are known to engulf the iron-based MR imaging contrast agent, ferumoxytol. Current ferumoxytol MR imaging techniques for localizing macrophages are confounded by contaminating intravascular signal. The aim of this study was to assess the utility of a newly developed MR imaging technique, segregation and extravascular localization of ferumoxytol imaging, for differentiating extravascular-from-intravascular ferumoxytol contrast signal at a delayed 24-hour imaging time point. MATERIALS AND METHODS Twenty-three patients with suspected post-chemoradiotherapy glioblastoma progression underwent ferumoxytol-enhanced SWI. Segregation and extravascular localization of ferumoxytol imaging maps were generated as the voxelwise difference of the delayed (24 hours) from the early (immediately after administration) time point SWI maps. Continuous segregation and extravascular localization of ferumoxytol imaging map values were separated into positive and negative components. Image-guided biologic correlation was performed. RESULTS Negative segregation and extravascular localization of ferumoxytol imaging values correlated with early and delayed time point SWI values, demonstrating that intravascular signal detected in the early time point persists into the delayed time point. Positive segregation and extravascular localization of ferumoxytol imaging values correlated only with delayed time point SWI values, suggesting successful detection of the newly developed extravascular signal. CONCLUSIONS Segregation and extravascular localization of ferumoxytol MR imaging improves on current techniques by eliminating intrinsic tissue and intravascular ferumoxytol signal and may inform glioblastoma outcomes by serving as a more specific metric of macrophage content compared with uncorrected T1 and SWI techniques.
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Affiliation(s)
- R F Barajas
- From the Departments of Radiology (R.F.B. Jr, D.S., B.E.H., J.S., D.R.P., J.P.N., J.M.P., L.S., C.G.V.)
- Advanced Imaging Research Center (R.F.B. Jr, D.S., X.L., A.H., W.D.R.)
- Knight Cancer Institute Translational Oncology Research Program (R.F.B. Jr)
| | - D Schwartz
- From the Departments of Radiology (R.F.B. Jr, D.S., B.E.H., J.S., D.R.P., J.P.N., J.M.P., L.S., C.G.V.)
- Advanced Imaging Research Center (R.F.B. Jr, D.S., X.L., A.H., W.D.R.)
| | - H L McConnell
- Departments of Neurology (H.L.M., C.N.K., L.S., C.G.V., P.A., L.L.M., E.A.N.)
- Blood-Brain Barrier Program (H.L.M., C.N.K., L.S., C.G.V., P.A., L.L.M., E.A.N.), Oregon Health & Science University, Portland, Oregon
| | - C N Kersch
- Departments of Neurology (H.L.M., C.N.K., L.S., C.G.V., P.A., L.L.M., E.A.N.)
- Blood-Brain Barrier Program (H.L.M., C.N.K., L.S., C.G.V., P.A., L.L.M., E.A.N.), Oregon Health & Science University, Portland, Oregon
| | - X Li
- Advanced Imaging Research Center (R.F.B. Jr, D.S., X.L., A.H., W.D.R.)
| | - B E Hamilton
- From the Departments of Radiology (R.F.B. Jr, D.S., B.E.H., J.S., D.R.P., J.P.N., J.M.P., L.S., C.G.V.)
| | - J Starkey
- From the Departments of Radiology (R.F.B. Jr, D.S., B.E.H., J.S., D.R.P., J.P.N., J.M.P., L.S., C.G.V.)
| | - D R Pettersson
- From the Departments of Radiology (R.F.B. Jr, D.S., B.E.H., J.S., D.R.P., J.P.N., J.M.P., L.S., C.G.V.)
| | - J P Nickerson
- From the Departments of Radiology (R.F.B. Jr, D.S., B.E.H., J.S., D.R.P., J.P.N., J.M.P., L.S., C.G.V.)
| | - J M Pollock
- From the Departments of Radiology (R.F.B. Jr, D.S., B.E.H., J.S., D.R.P., J.P.N., J.M.P., L.S., C.G.V.)
| | - R F Fu
- Medical Informatics and Clinical Epidemiology (R.F.F.)
| | - A Horvath
- Advanced Imaging Research Center (R.F.B. Jr, D.S., X.L., A.H., W.D.R.)
| | - L Szidonya
- From the Departments of Radiology (R.F.B. Jr, D.S., B.E.H., J.S., D.R.P., J.P.N., J.M.P., L.S., C.G.V.)
- Departments of Neurology (H.L.M., C.N.K., L.S., C.G.V., P.A., L.L.M., E.A.N.)
- Blood-Brain Barrier Program (H.L.M., C.N.K., L.S., C.G.V., P.A., L.L.M., E.A.N.), Oregon Health & Science University, Portland, Oregon
- Department of Diagnostic Radiology (L.S.), Heart and Vascular Center, Semmelweis University, Budapest, Hungary
| | - C G Varallyay
- From the Departments of Radiology (R.F.B. Jr, D.S., B.E.H., J.S., D.R.P., J.P.N., J.M.P., L.S., C.G.V.)
- Departments of Neurology (H.L.M., C.N.K., L.S., C.G.V., P.A., L.L.M., E.A.N.)
- Blood-Brain Barrier Program (H.L.M., C.N.K., L.S., C.G.V., P.A., L.L.M., E.A.N.), Oregon Health & Science University, Portland, Oregon
| | | | - A M Raslan
- Neurological Surgery (A.M.R., A.D., J.S.C., J.C., S.J.H., E.A.N.)
| | - A Dogan
- Neurological Surgery (A.M.R., A.D., J.S.C., J.C., S.J.H., E.A.N.)
| | - J S Cetas
- Neurological Surgery (A.M.R., A.D., J.S.C., J.C., S.J.H., E.A.N.)
| | - J Ciporen
- Neurological Surgery (A.M.R., A.D., J.S.C., J.C., S.J.H., E.A.N.)
| | - S J Han
- Neurological Surgery (A.M.R., A.D., J.S.C., J.C., S.J.H., E.A.N.)
| | - P Ambady
- Departments of Neurology (H.L.M., C.N.K., L.S., C.G.V., P.A., L.L.M., E.A.N.)
- Blood-Brain Barrier Program (H.L.M., C.N.K., L.S., C.G.V., P.A., L.L.M., E.A.N.), Oregon Health & Science University, Portland, Oregon
| | - L L Muldoon
- Departments of Neurology (H.L.M., C.N.K., L.S., C.G.V., P.A., L.L.M., E.A.N.)
- Blood-Brain Barrier Program (H.L.M., C.N.K., L.S., C.G.V., P.A., L.L.M., E.A.N.), Oregon Health & Science University, Portland, Oregon
| | | | - W D Rooney
- Advanced Imaging Research Center (R.F.B. Jr, D.S., X.L., A.H., W.D.R.)
| | - E A Neuwelt
- Departments of Neurology (H.L.M., C.N.K., L.S., C.G.V., P.A., L.L.M., E.A.N.)
- Neurological Surgery (A.M.R., A.D., J.S.C., J.C., S.J.H., E.A.N.)
- Blood-Brain Barrier Program (H.L.M., C.N.K., L.S., C.G.V., P.A., L.L.M., E.A.N.), Oregon Health & Science University, Portland, Oregon
- Portland Veterans Affairs Medical Center (E.A.N.), Portland, Oregon
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Ricard D, Durand T, Bompaire F, Tauziède-Espariat A, Psimaras D. Complicanze neurologiche della radioterapia. Neurologia 2020. [DOI: 10.1016/s1634-7072(20)43683-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022] Open
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46
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Barajas RF, Hamilton BE, Schwartz D, McConnell HL, Pettersson DR, Horvath A, Szidonya L, Varallyay CG, Firkins J, Jaboin JJ, Kubicky CD, Raslan AM, Dogan A, Cetas JS, Ciporen J, Han SJ, Ambady P, Muldoon LL, Woltjer R, Rooney WD, Neuwelt EA. Combined iron oxide nanoparticle ferumoxytol and gadolinium contrast enhanced MRI define glioblastoma pseudoprogression. Neuro Oncol 2020; 21:517-526. [PMID: 30277536 DOI: 10.1093/neuonc/noy160] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Noninvasively differentiating therapy-induced pseudoprogression from recurrent disease in patients with glioblastoma is prospectively difficult due to the current lack of a biologically specific imaging metric. Ferumoxytol iron oxide nanoparticle MRI contrast characterizes innate immunity mediated neuroinflammation; therefore, we hypothesized that combined ferumoxytol and gadolinium enhanced MRI could serve as a biomarker of glioblastoma pseudoprogression. METHODS In this institutional review board-approved, retrospective study, we analyzed ferumoxytol and gadolinium contrast enhanced T1-weighted 3T MRI in 45 patients with glioblastoma over multiple clinical timepoints. Isocitrate dehydrogenase 1 (IDH-1) mutational status was characterized by exome sequencing. Sum of products diameter measurements were calculated according to Response Assessment in Neuro-Oncology criteria from both gadolinium and ferumoxytol enhanced sequences. Enhancement mismatch was calculated as the natural log of the ferumoxytol to gadolinium sum of products diameter ratio. Analysis of variance and Student's t-test assessed differences in mismatch ratios. P-value <0.05 indicated statistical significance. RESULTS With the development of pseudoprogression we observed a significantly elevated mismatch ratio compared with disease recurrence (P < 0.01) within IDH-1 wild type patients. Patients with IDH-1 mutation demonstrated significantly reduced mismatch ratio with the development of pseudoprogression compared with disease recurrence (P < 0.01). Receiver operator curve analysis demonstrated 100% sensitivity and specificity for the use of mismatch ratios as a diagnostic biomarker of pseudoprogression. CONCLUSION Our study suggests that ferumoxytol to gadolinium contrast mismatch ratios are an MRI biomarker for the diagnosis of pseudoprogression in patients with glioblastoma. This may be due to the unique characterization of therapy-induced neuroinflammation.
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Affiliation(s)
- Ramon F Barajas
- Department of Radiology, Portland, Oregon.,Advanced Imaging Research Center, Portland, Oregon
| | | | - Daniel Schwartz
- Advanced Imaging Research Center, Portland, Oregon.,Department of Neurology, Portland, Oregon
| | | | | | | | | | - Csanad G Varallyay
- Department of Radiology, Portland, Oregon.,Department of Neurology, Portland, Oregon
| | | | | | | | | | | | | | | | | | | | | | - Randy Woltjer
- Department of Pathology, Oregon Health and Science University, Portland, Oregon
| | | | - Edward A Neuwelt
- Department of Neurology, Portland, Oregon.,Neurological Surgery, Portland, Oregon.,Portland Veterans Affairs Medical Center, Portland, Oregon
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Manning P, Daghighi S, Rajaratnam MK, Parthiban S, Bahrami N, Dale AM, Bolar D, Piccioni DE, McDonald CR, Farid N. Differentiation of progressive disease from pseudoprogression using 3D PCASL and DSC perfusion MRI in patients with glioblastoma. J Neurooncol 2020; 147:681-690. [PMID: 32239431 DOI: 10.1007/s11060-020-03475-y] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2019] [Accepted: 03/24/2020] [Indexed: 12/12/2022]
Abstract
PURPOSE To use 3D pseudocontinuous arterial spin labeling (3D PCASL) and dynamic susceptibility contrast-enhanced (DSC) perfusion MRI to differentiate progressive disease from pseudoprogression in patients with glioblastoma (GBM). METHODS Thirty-two patients with GBM who developed progressively enhancing lesions within the radiation field following resection and chemoradiation were included in this retrospective, single-institution study. The updated modified RANO criteria were used to establish progressive disease or pseudoprogression. Following 3D PCASL and DSC MR imaging, perfusion parameter estimates of cerebral blood flow (ASL-nCBF and DSC-nrCBF) and cerebral blood volume (DSC-nrCBV) were calculated. Additionally, contrast enhanced volumes were measured. Mann-Whitney U tests were used to compare groups. Linear discriminant analysis (LDA) and area under receiver operator characteristic curve (AUC) analyses were used to evaluate performance of each perfusion parameter and to determine optimal cut-off points. RESULTS All perfusion parameter measurements were higher in patients with progressive disease (mean, 95% CI ASL-nCBF 2.48, [2.03, 2.93]; DSC-nrCBF = 2.27, [1.85, 2.69]; DSC-nrCBV = 3.51, [2.37, 4.66]) compared to pseudoprogression (mean, 95% CI ASL-nCBF 0.99, [0.47, 1.52]; DSC-nrCBF = 1.05, [0.36, 1.74]; DSC-nCBV = 1.19, [0.34, 2.05]), and findings were significant at the p < 0.0125 level (p = 0.001, 0.003, 0.002; effect size: Cohen's d = 1.48, 1.27, and 0.92). Contrast enhanced volumes were not significantly different between groups (p > 0.447). All perfusion parameters demonstrated high AUC (0.954 for ASL-nCBF, 0.867 for DSC-nrCBF, and 0.891 for DSC-nrCBV), however, ASL-nCBF demonstrated the highest AUC and misclassified the fewest cases (N = 6). Lesions correctly classified by ASL but misclassified by DSC were located along the skull base or adjacent to large resection cavities with residual blood products, at areas of increased susceptibility. CONCLUSION Both 3D PCASL and DSC perfusion MRI techniques have nearly equivalent performance for the differentiation of progressive disease from pseudoprogression in patients with GBM. However, 3D PCASL is less sensitive to susceptibility artifact and may allow for improved classification in select cases.
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Affiliation(s)
- Paul Manning
- Department of Radiology, University of California, San Diego, La Jolla, CA, 92037, USA. .,Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, 92037, USA. .,Department of Radiology, University of California, San Diego, 200 West Arbor Drive, Mailbox # 8756, San Diego, CA, 92103, USA.
| | - Shadi Daghighi
- Department of Radiology, University of California, San Diego, La Jolla, CA, 92037, USA.,Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, 92037, USA
| | - Matthew K Rajaratnam
- Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, 92037, USA
| | - Sowmya Parthiban
- Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, 92037, USA
| | - Naeim Bahrami
- Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, 92037, USA
| | - Anders M Dale
- Department of Radiology, University of California, San Diego, La Jolla, CA, 92037, USA.,Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, 92037, USA.,Department of Neurosciences, University of California, San Diego, La Jolla, CA, 92037, USA
| | - Divya Bolar
- Department of Radiology, University of California, San Diego, La Jolla, CA, 92037, USA.,Center for Functional Magnetic Resonance Imaging, University of California, San Diego, La Jolla, CA, 92037, USA
| | - David E Piccioni
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, 92037, USA
| | - Carrie R McDonald
- Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, 92037, USA.,Department of Neurosciences, University of California, San Diego, La Jolla, CA, 92037, USA.,Department of Psychiatry, University of California, San Diego, La Jolla, CA, 92037, USA
| | - Nikdokht Farid
- Department of Radiology, University of California, San Diego, La Jolla, CA, 92037, USA.,Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, 92037, USA
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Jaramillo-Jiménez E, Gupta M, Snipes G, Cheek BS, Michael CB, Navarro-Montoya AM, Gómez-Escobar T, Jiménez-Villegas J, Rodríguez-Márquez I, Melguizo-Gavilanes I. Textiloma Mimicking a Recurrent High-Grade Astrocytoma: A Case Report. J Neurol Surg Rep 2020; 81:e7-e9. [PMID: 32206542 PMCID: PMC7085942 DOI: 10.1055/s-0039-3400231] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2019] [Accepted: 05/28/2019] [Indexed: 11/01/2022] Open
Abstract
Introduction Textiloma (Txm) is a nonmedical term that has been given to foreign body-related inflammatory pseudotumor arising from retained nonabsorbable cotton matrix that is either inadvertently or deliberately left behind during surgery, which may trigger an inflammatory reaction. This report describes a case of Txm mimicking a recurrent high-grade astrocytoma. Case Report We, here, present the case of a 69-year-old female with a 6-month history of progressive left-sided weakness. Neuroimaging studies revealed a large nonenhancing mass in the right frontoparietal lobe. Pathology reported a World Health Organization tumor classification grade II, diffuse astrocytoma. After surgical intervention, external beam radiation was given to the remaining areas of residual tumor. Routine magnetic resonance imaging (MRI) revealed a nodular area of contrast enhancement in the dorsal and inferior margin of the biopsy tract, growing between interval scans, and perfusion-weighted imaging parameters were elevated being clinically asymptomatic. She underwent a complete resection of this area of interest and pathology returned as a Txm with Surgicel fibers. Conclusion After treatment of a neoplasm, if unexpected clinical or imaging evidence of recurrence is present, a foreign body reaction to hemostatic material used during the initial surgery should be included in the differential diagnosis.
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Affiliation(s)
- Esteban Jaramillo-Jiménez
- Neuro-Oncology Unit, Instituto Neurológico de Colombia, Medellín, Antioquia, Colombia.,Facultad de Medicina, Universidad CES, Medellín, Antioquia, Colombia
| | - Manu Gupta
- Department of Radiology, Baylor University Medical Center at Dallas, Dallas, Texas, United States
| | - George Snipes
- Department of Pathology, Baylor University Medical Center at Dallas, Dallas, Texas, United States
| | - Brennen S Cheek
- Department of Radiation Oncology, Baylor University Medical Center at Dallas, Dallas, Texas, United States
| | - Christopher B Michael
- Department of Neurosurgery, Baylor University Medical Center at Dallas, Dallas, Texas, United States
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Rotkopf LT, Wiestler B, Preibisch C, Liesche-Starnecker F, Pyka T, Nörenberg D, Bette S, Gempt J, Thierfelder KM, Zimmer C, Huber T. The wavelet power spectrum of perfusion weighted MRI correlates with tumor vascularity in biopsy-proven glioblastoma samples. PLoS One 2020; 15:e0228030. [PMID: 31971966 PMCID: PMC6977746 DOI: 10.1371/journal.pone.0228030] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Accepted: 01/06/2020] [Indexed: 01/16/2023] Open
Abstract
Background Wavelet transformed reconstructions of dynamic susceptibility contrast (DSC) MR perfusion (wavelet-MRP) are a new and elegant way of visualizing vascularization. Wavelet-MRP maps yield a clear depiction of hypervascular tumor regions, as recently shown. Objective The aim of this study was to elucidate a possible connection of the wavelet-MRP power spectrum in glioblastoma (GBM) with local vascularity and cell proliferation. Methods For this IRB-approved study 12 patients (63.0+/-14.9y; 7m) with histologically confirmed IDH-wildtype GBM were included. Target regions for biopsies were prospectively marked on tumor regions as seen on preoperative 3T MRI. During subsequent neurosurgical tumor resection 43 targeted biopsies were taken from these target regions, of which all 27 matching samples were analyzed. All specimens were immunohistochemically analyzed for endothelial cell marker CD31 and proliferation marker Ki67 and correlated to the wavelet-MRP power spectrum as derived from DSC perfusion weighted imaging. Results There was a strong correlation between wavelet-MRP power spectrum (median = 4.41) and conventional relative cerebral blood volume (median = 5.97 ml/100g) in Spearman's rank-order correlation (κ = .83, p < .05). In a logistic regression model, the wavelet-MRP power spectrum showed a significant correlation to CD31 dichotomized to no or present staining (p = .04), while rCBV did not show a significant correlation to CD31 (p = .30). No significant association between Ki67 and rCBV or wavelet-MRP was found (p = .62 and p = .70, respectively). Conclusion The wavelet-MRP power spectrum derived from existing DSC-MRI data might be a promising new surrogate for tumor vascularity in GBM.
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Affiliation(s)
- Lukas T. Rotkopf
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technical University Munich, Munich, Germany
- * E-mail:
| | - Benedikt Wiestler
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technical University Munich, Munich, Germany
| | - Christine Preibisch
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technical University Munich, Munich, Germany
| | | | - Thomas Pyka
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technical University Munich, Munich, Germany
| | - Dominik Nörenberg
- Institute of Clinical Radiology and Nuclear Medicine, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Stefanie Bette
- Department of Diagnostic and Interventional Radiology and Neuroradiology, Universitaetsklinikum Augsburg, Augsburg, Germany
| | - Jens Gempt
- Department of Neurosurgery, Klinikum rechts der Isar, Technical University Munich, Munich, Germany
| | - Kolja M. Thierfelder
- Institute of Diagnostic and Interventional Radiology, Pediatric Radiology and Neuroradiology, University Medical Center Rostock, Rostock, Germany
| | - Claus Zimmer
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technical University Munich, Munich, Germany
| | - Thomas Huber
- Institute of Clinical Radiology and Nuclear Medicine, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
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50
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Li M, Tang H, Chan MD, Zhou X, Qian X. DC-AL GAN: Pseudoprogression and true tumor progression of glioblastoma multiform image classification based on DCGAN and AlexNet. Med Phys 2020; 47:1139-1150. [PMID: 31885094 DOI: 10.1002/mp.14003] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2019] [Revised: 12/16/2019] [Accepted: 12/17/2019] [Indexed: 12/19/2022] Open
Abstract
PURPOSE Pseudoprogression (PsP) occurs in 20-30% of patients with glioblastoma multiforme (GBM) after receiving the standard treatment. PsP exhibits similarities in shape and intensity to the true tumor progression (TTP) of GBM on the follow-up magnetic resonance imaging (MRI). These similarities pose challenges to the differentiation of these types of progression and hence the selection of the appropriate clinical treatment strategy. METHODS To address this challenge, we introduced a novel feature learning method based on deep convolutional generative adversarial network (DCGAN) and AlexNet, termed DC-AL GAN, to discriminate between PsP and TTP in MRI images. Due to the adversarial relationship between the generator and the discriminator of DCGAN, high-level discriminative features of PsP and TTP can be derived for the discriminator with AlexNet. We also constructed a multifeature selection module to concatenate features from different layers, contributing to more powerful features used for effectively discriminating between PsP and TTP. Finally, these discriminative features from the discriminator are used for classification by a support vector machine (SVM). Tenfold cross-validation (CV) and the area under the receiver operating characteristic (AUC) were applied to evaluate the performance of this developed algorithm. RESULTS The accuracy and AUC of DC-AL GAN for discriminating PsP and TTP after tenfold CV were 0.920 and 0.947. We also assessed the effects of different indicators (such as sensitivity and specificity) for features extracted from different layers to obtain a model with the best classification performance. CONCLUSIONS The proposed model DC-AL GAN is capable of learning discriminative representations from GBM datasets, and it achieves desirable PsP and TTP classification performance superior to other state-of-the-art methods. Therefore, the developed model would be useful in the diagnosis of PsP and TTP for GBM.
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Affiliation(s)
- Meiyu Li
- College of Electronic Science and Engineering, Jilin University, Changchun, 130012, China.,Institute for Medical Imaging Technology, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, China
| | - Hailiang Tang
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Michael D Chan
- Department of Radiology, Wake Forest School of Medicine, Winston-Salem, NC, 27157, USA
| | - Xiaobo Zhou
- School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Xiaohua Qian
- Institute for Medical Imaging Technology, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, China.,Department of Radiology, Wake Forest School of Medicine, Winston-Salem, NC, 27157, USA
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