• 18F-FACBC PET/MRI in diagnostic assessment and neurosurgery of gliomas 

      Karlberg, Anna Maria; Berntsen, Erik Magnus; Johansen, Håkon; Skjulsvik, Anne Jarstein; Reinertsen, Ingerid; Hong, Yan Dai; Xiao, Yiming; Rivaz, Hassan; Borghammer, Per; Solheim, Ole; Eikenes, Live (Peer reviewed; Journal article, 2019)
      Purpose: This pilot study aimed to evaluate the amino acid tracer 18F-FACBC with simultaneous PET/MRI in diagnostic assessment and neurosurgery of gliomas. Materials and Methods: Eleven patients with suspected primary ...
    • Are there predilection sites for intracranial meningioma? A population-based atlas 

      Hosainey, Sayied Abdol Mohieb; Bouget, David; Reinertsen, Ingerid; Sagberg, Lisa Millgård; Torp, Sverre Helge; Jakola, Asgeir Store; Solheim, Ole (Peer reviewed; Journal article, 2021)
      Meningioma is the most common benign intracranial tumor and is believed to arise from arachnoid cap cells of arachnoid granulations. We sought to develop a population-based atlas from pre-treatment MRIs to explore the ...
    • Automatic Intraoperative Correction of Brain Shift for Accurate Neuronavigation 

      Iversen, Daniel Høyer; Wein, Wolfgang; Lindseth, Frank; Unsgård, Geirmund; Reinertsen, Ingerid (Journal article; Peer reviewed, 2018)
      Background Unreliable neuronavigation owing to inaccurate patient-to-image registration and brain shift is a major problem in conventional magnetic resonance imaging–guided neurosurgery. We performed a prospective ...
    • Automatic intraoperative estimation of blood flow direction during neurosurgical interventions 

      Iversen, Daniel Høyer; Løvstakken, Lasse; Unsgård, Geirmund; Reinertsen, Ingerid (Journal article; Peer reviewed, 2018)
      Purpose In neurosurgery, reliable information about blood vessel anatomy and flow direction is important to identify, characterize, and avoid damage to the vasculature. Due to ultrasound Doppler angle dependencies and the ...
    • Brain atlas for assessing the impact of tumor location on perioperative quality of life in patients with high-grade glioma: A prospective population-based cohort study 

      Sagberg, Lisa Millgård; Iversen, Daniel Høyer; Fyllingen, Even Hovig; Jakola, Asgeir Store; Reinertsen, Ingerid; Solheim, Ole (Journal article; Peer reviewed, 2019)
      Background Tumor location is important for surgical decision making. Particular attention is paid to regions that contain sensorimotor and language functions, but it is unknown if these are the most important regions from ...
    • The Essential Role of Open Data and Software for the Future of Ultrasound-Based Neuronavigation 

      Reinertsen, Ingerid; Collins, D. Louis; Drouin, Simon (Peer reviewed; Journal article, 2020)
      With the recent developments in machine learning and modern graphics processing units (GPUs), there is a marked shift in the way intra-operative ultrasound (iUS) images can be processed and presented during surgery. Real-time ...
    • Evaluation of MRI to ultrasound registration methods for brain shift correction: The CuRIOUS2018 Challenge 

      Xiao, Yiming; Rivaz, Hassan; Chabanas, Matthieu; Fortin, Maryse; Machado, Ines; Ou, Yangming; Heinrich, Matthias P.; Schnabel, Julia; Zhong, Xia; Maier, Andreas; Wein, Wolfgang; Shams, Roozbeh; Kadoury, Samuel; Drobny, David; Modat, Marc; Reinertsen, Ingerid (Journal article; Peer reviewed, 2019)
    • FastPathology: An open-source platform for deep learning-based research and decision support in digital pathology 

      Pedersen, André; Valla, Marit; Bofin, Anna Mary; Perez de Frutos, Javier; Reinertsen, Ingerid; Smistad, Erik (Peer reviewed; Journal article, 2021)
      Deep convolutional neural networks (CNNs) are the current state-of-the-art for digital analysis of histopathological images. The large size of whole-slide microscopy images (WSIs) requires advanced memory handling to read, ...
    • Glioblastoma Segmentation: Comparison of Three Different Software Packages 

      Fyllingen, Even Hovig; Stensjøen, Anne Line; Berntsen, Erik Magnus; Reinertsen, Ingerid; Solheim, Ole (Journal article, 2016)
      To facilitate a more widespread use of volumetric tumor segmentation in clinical studies, there is an urgent need for reliable, user-friendly segmentation software. The aim of this study was therefore to compare three ...
    • Glioblastoma Surgery Imaging-Reporting and Data System: Validation and Performance of the Automated Segmentation Task 

      Bouget, David Nicolas Jean-Marie; Eijgelaar, Roelant; Pedersen, André; Kommers, Ivar; Ardon, Hilko; Barkhof, Frederik; Bello, Lorenzo; Berger, Mitchel S.; Nibali, Marco Conti; Furtner, Julia; Fyllingen, Even Hovig; Hervey-Jumper, Shawn; Idema, Albert J. S.; Kiesel, Barbara; Kloet, Alfred; Mandonnet, Emmanuel; Müller, Domenique M. J.; Robe, Pierre; Rossi, Marco; Sagberg, Lisa Millgård; Sciortino, Tommaso; van den Brink, Wimar A.; Wagemakers, Michiel; Widhalm, Georg; Witte, Marnix G.; Zwinderman, Aeilko H.; Reinertsen, Ingerid; Hamer, Philip C De Witt; Solheim, Ole (Peer reviewed; Journal article, 2021)
      For patients with presumed glioblastoma, essential tumor characteristics are determined from preoperative MR images to optimize the treatment strategy. This procedure is time-consuming and subjective, if performed by crude ...
    • Glioblastoma Surgery Imaging—Reporting and Data System: Standardized Reporting of Tumor Volume, Location, and Resectability Based on Automated Segmentations 

      Kommers, Ivar; Bouget, David Nicolas Jean-Marie; Pedersen, André; Eijgelaar, Roelant; Ardon, Hilko; Barkhof, Frederik; Bello, Lorenzo; Berger, Mitchel S.; Nibali, Marco Conti; Furtner, Julia; Fyllingen, Even Hovig; Hervey-Jumper, Shawn; Idema, Albert J. S.; Kiesel, Barbara; Kloet, Alfred; Mandonnet, Emmanuel; Müller, Domenique M. J.; Robe, Pierre; Rossi, Marco; Sagberg, Lisa Millgård; Sciortino, Tommaso; van den Brink, Wimar A.; Wagemakers, Michiel; Widhalm, Georg; Witte, Marnix G.; Zwinderman, Aeilko H.; Reinertsen, Ingerid; Solheim, Ole; De Witt Hamer, Philip C. (Peer reviewed; Journal article, 2021)
      Treatment decisions for patients with presumed glioblastoma are based on tumor characteristics available from a preoperative MR scan. Tumor characteristics, including volume, location, and resectability, are often estimated ...
    • Lower-Grade Gliomas: An Epidemiological Voxel-Based Analysis of Location and Proximity to Eloquent Regions 

      Gómez Vecchio, Tomás; Neimantaite, Alice; Corell, Alba; Bartek, Jiri; Jensdottir, Margret; Reinertsen, Ingerid; Solheim, Ole; Jakola, Asgeir S. (Peer reviewed; Journal article, 2021)
      Background: Glioma is the most common intra-axial tumor, and its location relative to critical areas of the brain is important for treatment decision-making. Studies often report tumor location based on anatomical taxonomy ...
    • Meningioma Segmentation in T1-Weighted MRI Leveraging Global Context and Attention Mechanisms 

      Bouget, David Nicolas Jean-Marie; Pedersen, André; Hosainey, Sayied Abdol Mohieb; Solheim, Ole; Reinertsen, Ingerid (Peer reviewed; Journal article, 2021)
      Purpose: Meningiomas are the most common type of primary brain tumor, accounting for ~30% of all brain tumors. A substantial number of these tumors are never surgically removed but rather monitored over time. Automatic and ...
    • Multimodal 18F-Fluciclovine PET/MRI and Ultrasound-Guided Neurosurgery of an Anaplastic Oligodendroglioma 

      Karlberg, Anna Maria; Berntsen, Erik Magnus; Johansen, Håkon; Myrthue, Mariane Olesen; Skjulsvik, Anne Jarstein; Reinertsen, Ingerid; Esmaeili, Morteza; Dai, Hong Yan; Xiao, Yiming; Rivaz, Hassan; Borghammer, Per; Solheim, Ole; Eikenes, Live (Journal article; Peer reviewed, 2017)
    • Nonlinear deformation of tractography in ultrasound-guided low-grade gliomas resection 

      Xiao, Yiming; Eikenes, Live; Reinertsen, Ingerid; Rivaz, Hassan (Journal article; Peer reviewed, 2018)
      Purpose In brain tumor surgeries, maximum removal of cancerous tissue without compromising normal brain functions can improve the patient’s survival rate and therapeutic benefits. To achieve this, diffusion MRI and ...
    • Quantitative texture analysis in the prediction of IDH status in low-grade gliomas. 

      Jakola, Asgeir Store; Zang, YH; Skjulsvik, Anne Jarstein; Solheim, Ole; Bø, Hans Kristian; Berntsen, Erik Magnus; Reinertsen, Ingerid; Gulati, Sasha; Förander, Petter; Brismar, Torkel B. (Journal article; Peer reviewed, 2017)
    • Registration of MR to Percutaneous Ultrasound of the Spine for Image-Guided Surgery 

      Bø, Lars Eirik; Palomar, Rafael; Selbekk, Tormod; Reinertsen, Ingerid (Chapter, 2014)
      One of the main limitations of today’s navigation systems for spine surgery is that they often are not available until after the bone surface has been exposed. Also, they lack the capability of soft tissue imaging, both ...
    • Spatial distribution of malignant transformation in patients with low-grade glioma 

      Jakola, Asgeir S; Bouget, David Nicolas Jean-Marie; Reinertsen, Ingerid; Skjulsvik, Anne Jarstein; Sagberg, Lisa Millgård; Bø, Hans Kristian; Gulati, Sasha; Sjåvik, Kristin; Solheim, Ole (Peer reviewed; Journal article, 2020)
      Background Malignant transformation represents the natural evolution of diffuse low-grade gliomas (LGG). This is a catastrophic event, causing neurocognitive symptoms, intensified treatment and premature death. However, ...
    • The diagnostic properties of intraoperative ultrasound in glioma surgery and factors associated with gross total tumor resection 

      Munkvold, Bodil Karoline Ravn; Jakola, Asgeir Store; Reinertsen, Ingerid; Sagberg, Lisa Millgård; Unsgård, Geirmund; Solheim, Ole (Journal article; Peer reviewed, 2018)
      Objective In glioma operations, we sought to analyze sensitivity, specificity, and predictive values of intraoperative 3-dimensional ultrasound (US) for detecting residual tumor compared with early postoperative magnetic ...
    • The Direction of Tumour Growth in Glioblastoma Patients 

      Esmaeili, Morteza; Stensjøen, Anne Line; Berntsen, Erik Magnus; Solheim, Ole; Reinertsen, Ingerid (Journal article; Peer reviewed, 2018)
      Generating MR-derived growth pattern models for glioblastoma multiforme (GBM) has been an attractive approach in neuro-oncology, suggesting a distinct pattern of lesion spread with a tendency in growing along the white ...