Asgeir Store Jakola1, Yi-Hua Zhang2, Anne J Skjulsvik3, Ole Solheim4, Hans Kristian Bø5, Erik Magnus Berntsen6, Ingerid Reinertsen7, Sasha Gulati8, Petter Förander9, Torkel B Brismar10. 1. Department of Neurosurgery, Sahlgrenska University Hospital, Gothenburg, Sweden; Institute of Neuroscience and Physiology, Sahlgrenska Academy, Gothenburg, Sweden; Department of Neurosurgery, St.Olavs University Hospital, Olav Kyrres Gate, 7006 Trondheim, Norway. Electronic address: legepost@gmail.com. 2. Department of Radiology, Karolinska University Hospital (Huddinge), Stockholm, Sweden; Division of Medical Imaging and Technology, Department of Clinical Science, Intervention and Technology (CLINTEC), Karolinska Institute, Stockholm, Sweden. Electronic address: yi-hua.zhang@ki.se. 3. Department of Pathology, St.Olavs University Hospital, Trondheim, Norway; Department of Laboratory Medicine, Children's and Women's Health, Norwegian University of Science and Technology, Trondheim, Norway. Electronic address: anne.j.skjulsvik@ntnu.no. 4. Department of Neurosurgery, St.Olavs University Hospital, Olav Kyrres Gate, 7006 Trondheim, Norway; National Norwegian Advisory Unit for Ultrasound and Image Guided Therapy, St.Olavs University Hospital, 7006 Trondheim Norway; Department of Neuromedicine and Movement Science, Medical Faculty, Norwegian University of Science and Technology, 7491 Trondheim, Norway. Electronic address: ole.solheim@ntnu.no. 5. Department of Radiology and Nuclear medicine, St.Olavs University Hospital, Olav Kyrres Gate, 7006 Trondheim, Norway; Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway. Electronic address: hanskrb@gmail.com. 6. Department of Radiology and Nuclear medicine, St.Olavs University Hospital, Olav Kyrres Gate, 7006 Trondheim, Norway; Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway. Electronic address: erik.berntsen@ntnu.no. 7. National Norwegian Advisory Unit for Ultrasound and Image Guided Therapy, St.Olavs University Hospital, 7006 Trondheim Norway; Department of Medical Technology, SINTEF, Trondheim, Norway. Electronic address: ingerid.reinertsen@sintef.no. 8. Department of Neurosurgery, St.Olavs University Hospital, Olav Kyrres Gate, 7006 Trondheim, Norway; Department of Neuromedicine and Movement Science, Medical Faculty, Norwegian University of Science and Technology, 7491 Trondheim, Norway. Electronic address: sasha.gulati@ntnu.no. 9. Department of Neurosurgery, Karolinska University Hospital, Stockholm, Sweden. Electronic address: petter.forander@karolinska.se. 10. Department of Radiology, Karolinska University Hospital (Huddinge), Stockholm, Sweden; Division of Medical Imaging and Technology, Department of Clinical Science, Intervention and Technology (CLINTEC), Karolinska Institute, Stockholm, Sweden. Electronic address: torkel.brismar@gmail.com.
Abstract
OBJECTIVES: Molecular markers provide valuable information about treatment response and prognosis in patients with low-grade gliomas (LGG). In order to make this important information available prior to surgery the aim of this study was to explore if molecular status in LGG can be discriminated by preoperative magnetic resonance imaging (MRI). PATIENTS AND METHODS: All patients with histopathologically confirmed LGG with available molecular status who had undergone a preoperative standard clinical MRI protocol using a 3T Siemens Skyra scanner during 2008-2015 were retrospectively identified. Based on Haralick texture parameters and the segmented LGG FLAIR volume we explored if it was possible to predict molecular status. RESULTS: In total 25 patients (nine women, average age 44) fulfilled the inclusion parameters. The textural parameter homogeneity could discriminate between LGG patients with IDH mutation (0.12, IQR 0.10-0.15) and IDH wild type (0.07, IQR 0.06-0.09, p=0.005). None of the other four analyzed texture parameters (energy, entropy, correlation and inertia) were associated with molecular status. Using ROC curves, the area under curve for predicting IDH mutation was 0.905 for homogeneity, 0.840 for tumor volume and 0.940 for the combined parameters of tumor volume and homogeneity. We could not predict molecular status using the four other chosen texture parameters (energy, entropy, correlation and inertia). Further, we could not separate LGG with IDH mutation with or without 1p19q codeletion. CONCLUSIONS: In this preliminary study using Haralick texture parameters based on preoperative clinical FLAIR sequence, the homogeneity parameter could separate IDH mutated LGG from IDH wild type LGG. Combined with tumor volume, these diagnostic properties seem promising.
OBJECTIVES: Molecular markers provide valuable information about treatment response and prognosis in patients with low-grade gliomas (LGG). In order to make this important information available prior to surgery the aim of this study was to explore if molecular status in LGG can be discriminated by preoperative magnetic resonance imaging (MRI). PATIENTS AND METHODS: All patients with histopathologically confirmed LGG with available molecular status who had undergone a preoperative standard clinical MRI protocol using a 3T Siemens Skyra scanner during 2008-2015 were retrospectively identified. Based on Haralick texture parameters and the segmented LGG FLAIR volume we explored if it was possible to predict molecular status. RESULTS: In total 25 patients (nine women, average age 44) fulfilled the inclusion parameters. The textural parameter homogeneity could discriminate between LGG patients with IDH mutation (0.12, IQR 0.10-0.15) and IDH wild type (0.07, IQR 0.06-0.09, p=0.005). None of the other four analyzed texture parameters (energy, entropy, correlation and inertia) were associated with molecular status. Using ROC curves, the area under curve for predicting IDH mutation was 0.905 for homogeneity, 0.840 for tumor volume and 0.940 for the combined parameters of tumor volume and homogeneity. We could not predict molecular status using the four other chosen texture parameters (energy, entropy, correlation and inertia). Further, we could not separate LGG with IDH mutation with or without 1p19q codeletion. CONCLUSIONS: In this preliminary study using Haralick texture parameters based on preoperative clinical FLAIR sequence, the homogeneity parameter could separate IDH mutated LGG from IDH wild type LGG. Combined with tumor volume, these diagnostic properties seem promising.
Authors: Minjae Kim; So Yeong Jung; Ji Eun Park; Yeongheun Jo; Seo Young Park; Soo Jung Nam; Jeong Hoon Kim; Ho Sung Kim Journal: Eur Radiol Date: 2019-12-11 Impact factor: 5.315
Authors: Brandon P Galm; Colleen Buckless; Brooke Swearingen; Martin Torriani; Anne Klibanski; Miriam A Bredella; Nicholas A Tritos Journal: Pituitary Date: 2020-06 Impact factor: 4.107
Authors: Jeanette E Eckel-Passow; Paul A Decker; Matt L Kosel; Thomas M Kollmeyer; Annette M Molinaro; Terri Rice; Alissa A Caron; Kristen L Drucker; Corinne E Praska; Melike Pekmezci; Helen M Hansen; Lucie S McCoy; Paige M Bracci; Bradley J Erickson; Claudia F Lucchinetti; Joseph L Wiemels; John K Wiencke; Melissa L Bondy; Beatrice Melin; Terry C Burns; Caterina Giannini; Daniel H Lachance; Margaret R Wrensch; Robert B Jenkins Journal: Neuro Oncol Date: 2019-03-18 Impact factor: 13.029