INTRODUCTION: The utility of surgical simulation with three-dimensional multimodality fusion imaging (3D-MFI) has been demonstrated. However, its potential in deep-seated brain lesions remains unknown. The aim of this study was to investigate the impact of 3D-MFI in deep-seated meningioma operations. MATERIAL AND METHODS: Fourteen patients with deeply located meningiomas were included in this study. We constructed 3D-MFIs by fusing high-resolution magnetic resonance (MR) and computed tomography (CT) images with a rotational digital subtraction angiogram (DSA) in all patients. The surgical procedure was simulated by 3D-MFI prior to operation. To assess the impact on neurosurgical education, the objective values of surgical simulation by 3D-MFIs/virtual reality (VR) video were evaluated. To validate the quality of 3D-MFIs, intraoperative findings were compared. The identification rate (IR) and positive predictive value (PPV) for the tumor feeding arteries and involved perforating arteries and veins were also assessed for quality assessment of 3D-MFI. RESULTS: After surgical simulation by 3D-MFIs, near-total resection was achieved in 13 of 14 (92.9%) patients without neurological complications. 3D-MFIs significantly contributed to the understanding of surgical anatomy and optimal surgical view (p < .0001) and learning how to preserve critical vessels (p < .0001) and resect tumors safety and extensively (p < .0001) by neurosurgical residents/fellows. The IR of 3D-MFI for tumor-feeding arteries and perforating arteries and veins was 100% and 92.9%, respectively. The PPV of 3D-MFI for tumor-feeding arteries and perforating arteries and veins was 98.8% and 76.5%, respectively. CONCLUSIONS: 3D-MFI contributed to learn skull base meningioma surgery. Also, 3D-MFI provided high quality to identify critical anatomical structures within or adjacent to deep-seated meningiomas. Thus, 3D-MFI is promising educational and surgical planning tool for meningiomas in deep-seated regions.
INTRODUCTION: The utility of surgical simulation with three-dimensional multimodality fusion imaging (3D-MFI) has been demonstrated. However, its potential in deep-seated brain lesions remains unknown. The aim of this study was to investigate the impact of 3D-MFI in deep-seated meningioma operations. MATERIAL AND METHODS: Fourteen patients with deeply located meningiomas were included in this study. We constructed 3D-MFIs by fusing high-resolution magnetic resonance (MR) and computed tomography (CT) images with a rotational digital subtraction angiogram (DSA) in all patients. The surgical procedure was simulated by 3D-MFI prior to operation. To assess the impact on neurosurgical education, the objective values of surgical simulation by 3D-MFIs/virtual reality (VR) video were evaluated. To validate the quality of 3D-MFIs, intraoperative findings were compared. The identification rate (IR) and positive predictive value (PPV) for the tumor feeding arteries and involved perforating arteries and veins were also assessed for quality assessment of 3D-MFI. RESULTS: After surgical simulation by 3D-MFIs, near-total resection was achieved in 13 of 14 (92.9%) patients without neurological complications. 3D-MFIs significantly contributed to the understanding of surgical anatomy and optimal surgical view (p < .0001) and learning how to preserve critical vessels (p < .0001) and resect tumors safety and extensively (p < .0001) by neurosurgical residents/fellows. The IR of 3D-MFI for tumor-feeding arteries and perforating arteries and veins was 100% and 92.9%, respectively. The PPV of 3D-MFI for tumor-feeding arteries and perforating arteries and veins was 98.8% and 76.5%, respectively. CONCLUSIONS: 3D-MFI contributed to learn skull base meningioma surgery. Also, 3D-MFI provided high quality to identify critical anatomical structures within or adjacent to deep-seated meningiomas. Thus, 3D-MFI is promising educational and surgical planning tool for meningiomas in deep-seated regions.
Authors: Lianne M Wellens; Jene Meulstee; Cornelis P van de Ven; C E J Terwisscha van Scheltinga; Annemieke S Littooij; Marry M van den Heuvel-Eibrink; Marta Fiocco; Anne C Rios; Thomas Maal; Marc H W A Wijnen Journal: JAMA Netw Open Date: 2019-04-05