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Yamin G, Tranvinh E, Lanzman BA, Tong E, Hashmi SS, Patel CB, Iv M. Arterial Spin-Labeling and DSC Perfusion Metrics Improve Agreement in Neuroradiologists' Clinical Interpretations of Posttreatment High-Grade Glioma Surveillance MR Imaging-An Institutional Experience. AJNR Am J Neuroradiol 2024; 45:453-460. [PMID: 38453410 PMCID: PMC11288557 DOI: 10.3174/ajnr.a8190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Accepted: 11/16/2023] [Indexed: 03/09/2024]
Abstract
BACKGROUND AND PURPOSE MR perfusion has shown value in the evaluation of posttreatment high-grade gliomas, but few studies have shown its impact on the consistency and confidence of neuroradiologists' interpretation in routine clinical practice. We evaluated the impact of adding MR perfusion metrics to conventional contrast-enhanced MR imaging in posttreatment high-grade glioma surveillance imaging. MATERIALS AND METHODS This retrospective study included 45 adults with high-grade gliomas who had posttreatment perfusion MR imaging. Four neuroradiologists assigned Brain Tumor Reporting and Data System scores for each examination on the basis of the interpretation of contrast-enhanced MR imaging and then after the addition of arterial spin-labeling-CBF, DSC-relative CBV, and DSC-fractional tumor burden. Interrater agreement and rater agreement with a multidisciplinary consensus group were assessed with κ statistics. Raters used a 5-point Likert scale to report confidence scores. The frequency of clinically meaningful score changes resulting from the addition of each perfusion metric was determined. RESULTS Interrater agreement was moderate for contrast-enhanced MR imaging alone (κ = 0.63) and higher with perfusion metrics (arterial spin-labeling-CBF, κ = 0.67; DSC-relative CBV, κ = 0.66; DSC-fractional tumor burden, κ = 0.70). Agreement between raters and consensus was highest with DSC-fractional tumor burden (κ = 0.66-0.80). Confidence scores were highest with DSC-fractional tumor burden. Across all raters, the addition of perfusion resulted in clinically meaningful interpretation changes in 2%-20% of patients compared with contrast-enhanced MR imaging alone. CONCLUSIONS Adding perfusion to contrast-enhanced MR imaging improved interrater agreement, rater agreement with consensus, and rater confidence in the interpretation of posttreatment high-grade glioma MR imaging, with the highest agreement and confidence scores seen with DSC-fractional tumor burden. Perfusion MR imaging also resulted in interpretation changes that could change therapeutic management in up to 20% of patients.
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Affiliation(s)
- Ghiam Yamin
- From the Department of Radiology (G.Y., E. Tranvinh, B.A.L., E. Tong, S.S.H., M.I.), Division of Neuroimaging and Neurointervention, Stanford University Medical Center, Stanford, California
| | - Eric Tranvinh
- From the Department of Radiology (G.Y., E. Tranvinh, B.A.L., E. Tong, S.S.H., M.I.), Division of Neuroimaging and Neurointervention, Stanford University Medical Center, Stanford, California
| | - Bryan A Lanzman
- From the Department of Radiology (G.Y., E. Tranvinh, B.A.L., E. Tong, S.S.H., M.I.), Division of Neuroimaging and Neurointervention, Stanford University Medical Center, Stanford, California
| | - Elizabeth Tong
- From the Department of Radiology (G.Y., E. Tranvinh, B.A.L., E. Tong, S.S.H., M.I.), Division of Neuroimaging and Neurointervention, Stanford University Medical Center, Stanford, California
| | - Syed S Hashmi
- From the Department of Radiology (G.Y., E. Tranvinh, B.A.L., E. Tong, S.S.H., M.I.), Division of Neuroimaging and Neurointervention, Stanford University Medical Center, Stanford, California
| | - Chirag B Patel
- Department of Neuro-Oncology (C.B.P.), The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Michael Iv
- From the Department of Radiology (G.Y., E. Tranvinh, B.A.L., E. Tong, S.S.H., M.I.), Division of Neuroimaging and Neurointervention, Stanford University Medical Center, Stanford, California
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Ehret F, Zühlke O, Schweizer L, Kahn J, Csapo-Schmidt C, Roohani S, Zips D, Capper D, Adeberg S, Abdollahi A, Knoll M, Kaul D. Validation of a methylation-based signature for subventricular zone involvement in glioblastoma. J Neurooncol 2024; 167:89-97. [PMID: 38376766 PMCID: PMC10978677 DOI: 10.1007/s11060-024-04570-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Accepted: 01/11/2024] [Indexed: 02/21/2024]
Abstract
PURPOSE Glioblastomas (GBM) with subventricular zone (SVZ) contact have previously been associated with a specific epigenetic fingerprint. We aim to validate a reported bulk methylation signature to determine SVZ contact. METHODS Methylation array analysis was performed on IDHwt GBM patients treated at our institution. The v11b4 classifier was used to ensure the inclusion of only receptor tyrosine kinase (RTK) I, II, and mesenchymal (MES) subtypes. Methylation-based assignment (SVZM ±) was performed using hierarchical cluster analysis. Magnetic resonance imaging (MRI) (T1ce) was independently reviewed for SVZ contact by three experienced readers. RESULTS Sixty-five of 70 samples were classified as RTK I, II, and MES. Full T1ce MRI-based rater consensus was observed in 54 cases, which were retained for further analysis. Epigenetic SVZM classification and SVZ were strongly associated (OR: 15.0, p = 0.003). Thirteen of fourteen differential CpGs were located in the previously described differentially methylated LRBA/MAB21L2 locus. SVZ + tumors were linked to shorter OS (hazard ratio (HR): 3.80, p = 0.02) than SVZM + at earlier time points (time-dependency of SVZM, p < 0.05). Considering the SVZ consensus as the ground truth, SVZM classification yields a sensitivity of 96.6%, specificity of 36.0%, positive predictive value (PPV) of 63.6%, and negative predictive value (NPV) of 90.0%. CONCLUSION Herein, we validated the specific epigenetic signature in GBM in the vicinity of the SVZ and highlighted the importance of methylation of a part of the LRBA/MAB21L2 gene locus. Whether SVZM can replace MRI-based SVZ assignment as a prognostic and diagnostic tool will require prospective studies of large, homogeneous cohorts.
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Affiliation(s)
- Felix Ehret
- Department of Radiation Oncology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, Berlin, Germany.
- Charité - Universitätsmedizin Berlin, Berlin, Germany; German Cancer Consortium (DKTK), partner site Berlin, and German Cancer Research Center (DKFZ), Heidelberg, Germany.
| | - Oliver Zühlke
- Department of Radiation Oncology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, Berlin, Germany
| | - Leonille Schweizer
- Institute of Neurology (Edinger Institute), University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany
| | - Johannes Kahn
- Department of Radiology, Health and Medical University, Potsdam, Germany
| | - Christoph Csapo-Schmidt
- Department of Neuroradiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, Berlin, Germany
| | - Siyer Roohani
- Department of Radiation Oncology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, 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, BIH Biomedical Innovation Academy, BIH Charité Junior Clinician Scientist Program, Berlin, Germany
| | - Daniel Zips
- Department of Radiation Oncology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, Berlin, Germany
- Charité - Universitätsmedizin Berlin, Berlin, Germany; German Cancer Consortium (DKTK), partner site Berlin, and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - David Capper
- Charité - Universitätsmedizin Berlin, Berlin, Germany; German Cancer Consortium (DKTK), partner site Berlin, and German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Neuropathology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, Berlin, Germany
| | - Sebastian Adeberg
- Department of Radiation Oncology, University Hospital Marburg/Gießen, Marburg, Germany
| | - Amir Abdollahi
- Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Maximilian Knoll
- Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - David Kaul
- Department of Radiation Oncology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, 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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Inter-rater reliability of retrograde urethrograms. World J Urol 2023; 41:1163-1167. [PMID: 36800013 DOI: 10.1007/s00345-023-04323-0] [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: 11/05/2022] [Accepted: 01/30/2023] [Indexed: 02/18/2023] Open
Abstract
PURPOSE Reliability of pre-operative testing is important for adequate surgical planning. For urethral stricture disease, preoperative planning frequently includes retrograde urethrogram (RUG). The radiographic interpretation of RUGs is often done by urologists themselves. We aimed to evaluate the reliability of RUG interpretation by urologists at our institution. METHODS We examined the RUGs of 193 patients. These were deidentified and interpreted by three urologists, two general urologists and one reconstructive urologist. These interpretations were compared in 2 ways. Each of the general urologists was compared to the "gold standard" reconstructive urologist interpretation, and the general urologists were additionally compared to each other. We used intraclass correlation coefficient (ICC) for numerical variables and Fleiss' Kappa or Cohen's Kappa statistic (κ) for categorical variables to rate inter-interpreter reliability and agreement among interpretations with regards to the quantitative variables of stricture length and caliber. RESULTS Level of agreement ranged from poor to moderate across all variables interpreted. Comparing general urologists to the gold standard yielded no better than moderate agreement, with the majority being poor to fair. Similarly, agreement amongst the general urologists did not reach above moderate, with the majority being poor to slight. CONCLUSION To our knowledge, this is the first analysis of inter-rater reliability of RUGs among practicing urologists. Our analysis showed clinically unacceptable reliability with regards to stricture length, location, caliber, and indicated procedures. This study suggests a need for standardized interpretation of RUGs and poses an opportunity for actionable improvement in management of strictures.
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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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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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Zakhari N, Taccone M, Torres C, Chakraborty S, Sinclair J, Woulfe J, Jansen G, Cron G, Nguyen TB. Qualitative Assessment of Advanced MRI in Post-Treatment High Grade Gliomas Follow Up: Do We Agree? Can Assoc Radiol J 2021; 73:187-193. [PMID: 33998827 DOI: 10.1177/08465371211013568] [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] [Indexed: 11/15/2022] Open
Abstract
PURPOSE MRI is commonly used in follow up of high grade glioma. Our purpose is to assess the interrater agreement on the increasingly used visual qualitative assessment of various conventional and advanced MR techniques in the setting of treated high grade glioma in comparison to the well established quantitative measurements. METHODS We prospectively enrolled HGG patients who underwent reresection of a new enhancing lesion on post-treatment 3T MR examination including DWI, DCE and DSC sequences. Two neuroradiologists objectively assessed the diffusion and perfusion maps by placing ROI on representative post-processed maps. They subjectively assessed the post-contrast, perfusion and diffusion sequences. Interrater agreement and concordance correlation coefficient were calculated. RESULTS Twenty-eight lesions were included. The interrater agreement on the qualitative assessment was good for k-trans (k = 0.73), moderate for Vp (k = 0.52), fair for AUC and Ve maps (k = 0.37 and 0.21), fair for corrected CBV (k = 0.39) and poor for the enhancement pattern and presence of diffusion restriction (k = 0.02 and 0.07). The concordance between the quantitative measurements was substantial for AUC and Vp (ρc = 0.98 and 0.97), moderate for k-trans and corrected CBV (ρc = 0.94) and poor for Ve and ADC (ρc = 0.86 and 0.24). CONCLUSION While the quantitative measurements of DSC and DCE perfusion maps show satisfactory inter-rater agreement, the qualitative assessment has lower interobserver agreement and should not be relied upon solely in the interpretation. Similarly, the suboptimal inter-rater agreement on the interpretation of enhancement pattern and diffusion restriction potentially limits their usefulness in differentiating glioma recurrence from treatment related changes.
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Affiliation(s)
- Nader Zakhari
- Division of Neuroradiology, Department of Radiology, University of Ottawa, The Ottawa Hospital Civic and General Campus, Ottawa, Ontario, Canada
| | - Michael Taccone
- Division of Neurosurgery, Department of Surgery, University of Ottawa, The Ottawa Hospital Civic and General Campus, Ottawa, Ontario
| | - Carlos Torres
- Division of Neuroradiology, Department of Radiology, University of Ottawa, The Ottawa Hospital Civic and General Campus, Ottawa, Ontario, Canada
- The Ottawa Hospital Research Institute, Ottawa, Ontario, Canada
| | - Santanu Chakraborty
- Division of Neuroradiology, Department of Radiology, University of Ottawa, The Ottawa Hospital Civic and General Campus, Ottawa, Ontario, Canada
- The Ottawa Hospital Research Institute, Ottawa, Ontario, Canada
| | - John Sinclair
- Division of Neurosurgery, Department of Surgery, University of Ottawa, The Ottawa Hospital Civic and General Campus, Ottawa, Ontario
| | - John Woulfe
- The Ottawa Hospital Research Institute, Ottawa, Ontario, Canada
- Department of Pathology, University of Ottawa, The Ottawa Hospital Civic and General Campus, Ottawa, Ontario, Canada
| | - Gerard Jansen
- The Ottawa Hospital Research Institute, Ottawa, Ontario, Canada
- Department of Pathology, University of Ottawa, The Ottawa Hospital Civic and General Campus, Ottawa, Ontario, Canada
| | - Greg Cron
- Department of Neurology, Stanford School of Medicine, Menlo Park, California, USA
| | - Thanh B Nguyen
- Division of Neuroradiology, Department of Radiology, University of Ottawa, The Ottawa Hospital Civic and General Campus, Ottawa, Ontario, Canada
- The Ottawa Hospital Research Institute, Ottawa, Ontario, Canada
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Steed TC, Treiber JM, Taha B, Engin HB, Carter H, Patel KS, Dale AM, Carter BS, Chen CC. Glioblastomas located in proximity to the subventricular zone (SVZ) exhibited enrichment of gene expression profiles associated with the cancer stem cell state. J Neurooncol 2020; 148:455-462. [PMID: 32556864 DOI: 10.1007/s11060-020-03550-4] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Accepted: 05/29/2020] [Indexed: 02/07/2023]
Abstract
INTRODUCTION Conflicting results have been reported in the association between glioblastoma proximity to the subventricular zone (SVZ) and enrichment of cancer stem cell properties. Here, we examined this hypothesis using magnetic resonance (MR) images derived from 217 The Cancer Imaging Archive (TCIA) glioblastoma subjects. METHODS Pre-operative MR images were segmented automatically into contrast enhancing (CE) tumor volumes using Iterative Probabilistic Voxel Labeling (IPVL). Distances were calculated from the centroid of CE tumor volumes to the SVZ and correlated with gene expression profiles of the corresponding glioblastomas. Correlative analyses were performed between SVZ distance, gene expression patterns, and clinical survival. RESULTS Glioblastoma located in proximity to the SVZ showed increased mRNA expression patterns associated with the cancer stem-cell state, including CD133 (P = 0.006). Consistent with the previous observations suggesting that glioblastoma stem cells exhibit increased DNA repair capacity, glioblastomas in proximity to the SVZ also showed increased expression of DNA repair genes, including MGMT (P = 0.018). Reflecting this enhanced DNA repair capacity, the genomes of glioblastomas in SVZ proximity harbored fewer single nucleotide polymorphisms relative to those located distant to the SVZ (P = 0.003). Concordant with the notion that glioblastoma stem cells are more aggressive and refractory to therapy, patients with glioblastoma in proximity to SVZ exhibited poorer progression free and overall survival (P < 0.01). CONCLUSION An unbiased analysis of TCIA suggests that glioblastomas located in proximity to the SVZ exhibited mRNA expression profiles associated with stem cell properties, increased DNA repair capacity, and is associated with poor clinical survival.
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Affiliation(s)
- Tyler C Steed
- Department of Neurosurgery, Emory School of Surgery, Atlanta, GA, USA
| | - Jeffrey M Treiber
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Birra Taha
- Department of Neurosurgery, University of Minnesota, D429 Mayo Memorial Building, 420 Delaware St. S. E., MMC96, Minneapolis, MN, 55455, USA
| | - H Billur Engin
- Division of Medical Genetics, Department of Medicine, University of California, La Jolla, San Diego, CA, USA
| | - Hannah Carter
- Division of Medical Genetics, Department of Medicine, University of California, La Jolla, San Diego, CA, USA
| | - Kunal S Patel
- Department of Neurosurgery, University of California Los Angeles, Los Angeles, CA, USA
| | - Anders M Dale
- Multimodal Imaging Laboratory, University of California San Diego, La Jolla, San Diego, CA, USA
- Department of Radiology, University of California San Diego, La Jolla, San Diego, CA, USA
| | - Bob S Carter
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA
| | - Clark C Chen
- Department of Neurosurgery, University of Minnesota, D429 Mayo Memorial Building, 420 Delaware St. S. E., MMC96, Minneapolis, MN, 55455, USA.
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Fathallah-Shaykh HM, DeAtkine A, Coffee E, Khayat E, Bag AK, Han X, Warren PP, Bredel M, Fiveash J, Markert J, Bouaynaya N, Nabors LB. Diagnosing growth in low-grade gliomas with and without longitudinal volume measurements: A retrospective observational study. PLoS Med 2019; 16:e1002810. [PMID: 31136584 PMCID: PMC6538148 DOI: 10.1371/journal.pmed.1002810] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Accepted: 04/22/2019] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND Low-grade gliomas cause significant neurological morbidity by brain invasion. There is no universally accepted objective technique available for detection of enlargement of low-grade gliomas in the clinical setting; subjective evaluation by clinicians using visual comparison of longitudinal radiological studies is the gold standard. The aim of this study is to determine whether a computer-assisted diagnosis (CAD) method helps physicians detect earlier growth of low-grade gliomas. METHODS AND FINDINGS We reviewed 165 patients diagnosed with grade 2 gliomas, seen at the University of Alabama at Birmingham clinics from 1 July 2017 to 14 May 2018. MRI scans were collected during the spring and summer of 2018. Fifty-six gliomas met the inclusion criteria, including 19 oligodendrogliomas, 26 astrocytomas, and 11 mixed gliomas in 30 males and 26 females with a mean age of 48 years and a range of follow-up of 150.2 months (difference between highest and lowest values). None received radiation therapy. We also studied 7 patients with an imaging abnormality without pathological diagnosis, who were clinically stable at the time of retrospective review (14 May 2018). This study compared growth detection by 7 physicians aided by the CAD method with retrospective clinical reports. The tumors of 63 patients (56 + 7) in 627 MRI scans were digitized, including 34 grade 2 gliomas with radiological progression and 22 radiologically stable grade 2 gliomas. The CAD method consisted of tumor segmentation, computing volumes, and pointing to growth by the online abrupt change-of-point method, which considers only past measurements. Independent scientists have evaluated the segmentation method. In 29 of the 34 patients with progression, the median time to growth detection was only 14 months for CAD compared to 44 months for current standard of care radiological evaluation (p < 0.001). Using CAD, accurate detection of tumor enlargement was possible with a median of only 57% change in the tumor volume as compared to a median of 174% change of volume necessary to diagnose tumor growth using standard of care clinical methods (p < 0.001). In the radiologically stable group, CAD facilitated growth detection in 13 out of 22 patients. CAD did not detect growth in the imaging abnormality group. The main limitation of this study was its retrospective design; nevertheless, the results depict the current state of a gold standard in clinical practice that allowed a significant increase in tumor volumes from baseline before detection. Such large increases in tumor volume would not be permitted in a prospective design. The number of glioma patients (n = 56) is a limitation; however, it is equivalent to the number of patients in phase II clinical trials. CONCLUSIONS The current practice of visual comparison of longitudinal MRI scans is associated with significant delays in detecting growth of low-grade gliomas. Our findings support the idea that physicians aided by CAD detect growth at significantly smaller volumes than physicians using visual comparison alone. This study does not answer the questions whether to treat or not and which treatment modality is optimal. Nonetheless, early growth detection sets the stage for future clinical studies that address these questions and whether early therapeutic interventions prolong survival and improve quality of life.
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Affiliation(s)
- Hassan M. Fathallah-Shaykh
- Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
- Department of Mathematics, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
- * E-mail:
| | - Andrew DeAtkine
- Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - Elizabeth Coffee
- Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - Elias Khayat
- Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - Asim K. Bag
- Department of Diagnostic Imaging, St. Jude Children’s Research Hospital, Memphis, Tennessee, United States of America
| | - Xiaosi Han
- Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - Paula Province Warren
- Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - Markus Bredel
- Department of Radiation Oncology, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - John Fiveash
- Department of Radiation Oncology, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - James Markert
- Department of Neurological Surgery, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - Nidhal Bouaynaya
- Department of Electrical Engineering, Rowan University, Glassboro, New Jersey, United States of America
| | - Louis B. Nabors
- Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
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Ciritsis A, Boss A, Rossi C. Automated pixel-wise brain tissue segmentation of diffusion-weighted images via machine learning. NMR IN BIOMEDICINE 2018; 31:e3931. [PMID: 29697165 DOI: 10.1002/nbm.3931] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/27/2017] [Revised: 02/27/2018] [Accepted: 03/09/2018] [Indexed: 06/08/2023]
Abstract
The diffusion-weighted (DW) MR signal sampled over a wide range of b-values potentially allows for tissue differentiation in terms of cellularity, microstructure, perfusion, and T2 relaxivity. This study aimed to implement a machine learning algorithm for automatic brain tissue segmentation from DW-MRI datasets, and to determine the optimal sub-set of features for accurate segmentation. DWI was performed at 3 T in eight healthy volunteers using 15 b-values and 20 diffusion-encoding directions. The pixel-wise signal attenuation, as well as the trace and fractional anisotropy (FA) of the diffusion tensor, were used as features to train a support vector machine classifier for gray matter, white matter, and cerebrospinal fluid classes. The datasets of two volunteers were used for validation. For each subject, tissue classification was also performed on 3D T1 -weighted data sets with a probabilistic framework. Confusion matrices were generated for quantitative assessment of image classification accuracy in comparison with the reference method. DWI-based tissue segmentation resulted in an accuracy of 82.1% on the validation dataset and of 82.2% on the training dataset, excluding relevant model over-fitting. A mean Dice coefficient (DSC) of 0.79 ± 0.08 was found. About 50% of the classification performance was attributable to five features (i.e. signal measured at b-values of 5/10/500/1200 s/mm2 and the FA). This reduced set of features led to almost identical performances for the validation (82.2%) and the training (81.4%) datasets (DSC = 0.79 ± 0.08). Machine learning techniques applied to DWI data allow for accurate brain tissue segmentation based on both morphological and functional information.
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Affiliation(s)
- Alexander Ciritsis
- Department of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Switzerland
| | - Andreas Boss
- Department of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Switzerland
| | - Cristina Rossi
- Department of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Switzerland
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Kerkhof M, Ganeff I, Wiggenraad RGJ, Lycklama À Nijeholt GJ, Hammer S, Taphoorn MJB, Dirven L, Vos MJ. Clinical applicability of and changes in perfusion MR imaging in brain metastases after stereotactic radiotherapy. J Neurooncol 2018; 138:133-139. [PMID: 29392588 PMCID: PMC5928168 DOI: 10.1007/s11060-018-2779-7] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2017] [Accepted: 01/25/2018] [Indexed: 12/05/2022]
Abstract
To assess the applicability of perfusion-weighted (PWI) magnetic resonance (MR) imaging in clinical practice, as well as to evaluate the changes in PWI in brain metastases before and after stereotactic radiotherapy (SRT), and to correlate these changes to tumor status on conventional MR imaging. Serial MR images at baseline and at least 3 and 6 months after SRT were retrospectively evaluated. Size of metastases and the relative cerebral blood volume (rCBV), assessed with subjective visual inspection in the contrast enhanced area, were evaluated at each time point. Tumor behavior of metastases was categorized into four groups based on predefined changes on MRI during follow-up, or on histologically confirmed diagnosis; progressive disease (PD), pseudoprogression (PsPD), non-progressive disease (non-PD) and progression unspecified (PU). Twenty-six patients with 42 metastases were included. Fifteen percent (26/168) of all PW images could not be evaluated due to localization near large vessels or the scalp, presence of hemorrhage artefacts, and in 31% (52/168) due to unmeasurable residual metastases. The most common pattern (52%, 13/25 metastases) showed a high rCBV at baseline and low rCBV during follow-up, occurring in metastases with non-PD (23%, 3/13), PsPD (38%, 5/13) and PU (38%, 5/13). Including only metastases with a definite outcome generally showed low rCBV in PsPD or non-PD, and high rCBV in PD. Although non-PD and PsPD may be distinguished from PD after SRT using the PW images, the large proportion of images that could not be assessed due to artefacts and size severely hampers value of PWI in predicting tumor response after SRT.
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Affiliation(s)
- M Kerkhof
- Department of Neurology, Haaglanden Medical Center, PO Box 432, 2501 CK, The Hague, The Netherlands.
| | - I Ganeff
- Department of Neurology, Haaglanden Medical Center, PO Box 432, 2501 CK, The Hague, The Netherlands
| | - R G J Wiggenraad
- Department of Radiotherapy, Haaglanden Medical Center, The Hague, The Netherlands
| | | | - S Hammer
- Department of Radiology, Haaglanden Medical Center, The Hague, The Netherlands
| | - M J B Taphoorn
- Department of Neurology, Haaglanden Medical Center, PO Box 432, 2501 CK, The Hague, The Netherlands.,Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands
| | - L Dirven
- Department of Neurology, Haaglanden Medical Center, PO Box 432, 2501 CK, The Hague, The Netherlands.,Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands
| | - M J Vos
- Department of Neurology, Haaglanden Medical Center, PO Box 432, 2501 CK, The Hague, The Netherlands
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Razek AAKA, El-Serougy L, Abdelsalam M, Gaballa G, Talaat M. Differentiation of residual/recurrent gliomas from postradiation necrosis with arterial spin labeling and diffusion tensor magnetic resonance imaging-derived metrics. Neuroradiology 2017; 60:169-177. [PMID: 29218370 DOI: 10.1007/s00234-017-1955-3] [Citation(s) in RCA: 88] [Impact Index Per Article: 12.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2017] [Accepted: 11/27/2017] [Indexed: 12/25/2022]
Abstract
PURPOSE The aim of this study is to differentiate recurrent/residual gliomas from postradiation changes using arterial spin labeling (ASL) perfusion and diffusion tensor imaging (DTI)-derived metrics. METHODS Prospective study was conducted upon 42 patients with high-grade gliomas after radiotherapy only or prior to other therapies that underwent routine MR imaging, ASL, and DTI. The tumor blood flow (TBF), fractional anisotropy (FA), and mean diffusivity (MD) of the enhanced lesion and related edema were calculated. The lesion was categorized as recurrence/residual or postradiation changes. RESULTS There was significant differences between residual/recurrent gliomas and postradiation changes of TBF (P = 0.001), FA (P = 0.001 and 0.04), and MD (P = 0.001) of enhanced lesion and related edema respectively. The area under the curve (AUC) of TBF of enhanced lesion and related edema used to differentiate residual/recurrent gliomas from postradiation changes were 0.95 and 0.93 and of MD were 0.95 and 0.81 and of FA were 0.81 and 0.695, respectively. Combined ASL and DTI metrics of the enhanced lesion revealed AUC of 0.98, accuracy of 95%, sensitivity of 93.8%, specificity of 95.8%, positive predictive value (PPV) of 93.8%, and negative predictive value (NPV) of 95.8%. Combined metrics of ASL and DTI of related edema revealed AUC of 0.97, accuracy of 92.5%, sensitivity of 93.8%, specificity of 91.7%, PPV of 88.2%, and NPV of 95.7. CONCLUSION Combined ASL and DTI metrics of enhanced lesion and related edema are valuable noninvasive tools in differentiating residual/recurrent gliomas from postradiation changes.
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Affiliation(s)
| | - Lamiaa El-Serougy
- Department of Diagnostic Radiology, Mansoura Faculty of Medicine, Mansoura, 13551, Egypt
| | | | - Gada Gaballa
- Department of Diagnostic Radiology, Mansoura Faculty of Medicine, Mansoura, 13551, Egypt
| | - Mona Talaat
- Department of Diagnostic Radiology, Mansoura Faculty of Medicine, Mansoura, 13551, Egypt
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Schapira AHV. Advances and insights into neurological practice 2016−17. Eur J Neurol 2017; 24:1425-1434. [DOI: 10.1111/ene.13480] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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Huber T, Alber G, Bette S, Kaesmacher J, Boeckh-Behrens T, Gempt J, Ringel F, Specht HM, Meyer B, Zimmer C, Wiestler B, Kirschke JS. Progressive disease in glioblastoma: Benefits and limitations of semi-automated volumetry. PLoS One 2017; 12:e0173112. [PMID: 28245291 PMCID: PMC5330491 DOI: 10.1371/journal.pone.0173112] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2016] [Accepted: 02/15/2017] [Indexed: 11/18/2022] Open
Abstract
Purpose Unambiguous evaluation of glioblastoma (GB) progression is crucial, both for clinical trials as well as day by day routine management of GB patients. 3D-volumetry in the follow-up of GB provides quantitative data on tumor extent and growth, and therefore has the potential to facilitate objective disease assessment. The present study investigated the utility of absolute changes in volume (delta) or regional, segmentation-based subtractions for detecting disease progression in longitudinal MRI follow-ups. Methods 165 high resolution 3-Tesla MRIs of 30 GB patients (23m, mean age 60.2y) were retrospectively included in this single center study. Contrast enhancement (CV) and tumor-related signal alterations in FLAIR images (FV) were semi-automatically segmented. Delta volume (dCV, dFV) and regional subtractions (sCV, sFV) were calculated. Disease progression was classified for every follow-up according to histopathologic results, decisions of the local multidisciplinary CNS tumor board and a consensus rating of the neuro-radiologic report. Results A generalized logistic mixed model for disease progression (yes / no) with dCV, dFV, sCV and sFV as input variables revealed that only dCV was significantly associated with prediction of disease progression (P = .005). Delta volume had a better accuracy than regional, segmentation-based subtractions (79% versus 72%) and a higher area under the curve by trend in ROC curves (.83 versus .75). Conclusion Absolute volume changes of the contrast enhancing tumor part were the most accurate volumetric determinant to detect progressive disease in assessment of GB and outweighed FLAIR changes as well as regional, segmentation-based image subtractions. This parameter might be useful in upcoming objective response criteria for glioblastoma.
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Affiliation(s)
- Thomas Huber
- Department of Neuroradiology, Klinikum rechts der Isar, Technical University of Munich, Germany
- Institute for Clinical Radiology, Ludwig-Maximilians-University Hospital, Munich, Germany
| | - Georgina Alber
- Department of Neuroradiology, Klinikum rechts der Isar, Technical University of Munich, Germany
| | - Stefanie Bette
- Department of Neuroradiology, Klinikum rechts der Isar, Technical University of Munich, Germany
| | - Johannes Kaesmacher
- Department of Neuroradiology, Klinikum rechts der Isar, Technical University of Munich, Germany
| | - Tobias Boeckh-Behrens
- Department of Neuroradiology, Klinikum rechts der Isar, Technical University of Munich, Germany
| | - Jens Gempt
- Department of Neurosurgery, Klinikum rechts der Isar, Technical University of Munich, Germany
| | - Florian Ringel
- Department of Neurosurgery, Klinikum rechts der Isar, Technical University of Munich, Germany
| | - Hanno M. Specht
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich, Germany
| | - Bernhard Meyer
- Department of Neurosurgery, Klinikum rechts der Isar, Technical University of Munich, Germany
| | - Claus Zimmer
- Department of Neuroradiology, Klinikum rechts der Isar, Technical University of Munich, Germany
| | - Benedikt Wiestler
- Department of Neuroradiology, Klinikum rechts der Isar, Technical University of Munich, Germany
| | - Jan S. Kirschke
- Department of Neuroradiology, Klinikum rechts der Isar, Technical University of Munich, Germany
- * E-mail:
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