PubMed:27796600 JSONTXT

{"project":"PubMed_Structured_Abstracts","denotations":[{"id":"T1","span":{"begin":170,"end":875},"obj":"BACKGROUND"},{"id":"T2","span":{"begin":885,"end":1644},"obj":"METHODS"},{"id":"T3","span":{"begin":1654,"end":2079},"obj":"RESULTS"},{"id":"T4","span":{"begin":2093,"end":2342},"obj":"CONCLUSIONS"}],"text":"Robust augmented reality registration method for localization of solid organs' tumors using CT-derived virtual biomechanical model and fluorescent fiducials.\nBACKGROUND: Augmented reality (AR) is the fusion of computer-generated and real-time images. AR can be used in surgery as a navigation tool, by creating a patient-specific virtual model through 3D software manipulation of DICOM imaging (e.g., CT scan). The virtual model can be superimposed to real-time images enabling transparency visualization of internal anatomy and accurate localization of tumors. However, the 3D model is rigid and does not take into account inner structures' deformations. We present a concept of automated AR registration, while the organs undergo deformation during surgical manipulation, based on finite element modeling (FEM) coupled with optical imaging of fluorescent surface fiducials.\nMETHODS: Two 10 × 1 mm wires (pseudo-tumors) and six 10 × 0.9 mm fluorescent fiducials were placed in ex vivo porcine kidneys (n = 10). Biomechanical FEM-based models were generated from CT scan. Kidneys were deformed and the shape changes were identified by tracking the fiducials, using a near-infrared optical system. The changes were registered automatically with the virtual model, which was deformed accordingly. Accuracy of prediction of pseudo-tumors' location was evaluated with a CT scan in the deformed status (ground truth). In vivo: fluorescent fiducials were inserted under ultrasound guidance in the kidney of one pig, followed by a CT scan. The FEM-based virtual model was superimposed on laparoscopic images by automatic registration of the fiducials.\nRESULTS: Biomechanical models were successfully generated and accurately superimposed on optical images. The mean measured distance between the estimated tumor by biomechanical propagation and the scanned tumor (ground truth) was 0.84 ± 0.42 mm. All fiducials were successfully placed in in vivo kidney and well visualized in near-infrared mode enabling accurate automatic registration of the virtual model on the laparoscopic images.\nCONCLUSIONS: Our preliminary experiments showed the potential of a biomechanical model with fluorescent fiducials to propagate the deformation of solid organs' surface to their inner structures including tumors with good accuracy and automatized robust tracking."}

{"project":"Goldhamster2_Cellosaurus","denotations":[{"id":"T1","span":{"begin":238,"end":242},"obj":"CVCL_0047|Telomerase_immortalized_cell_line|Homo sapiens"},{"id":"T2","span":{"begin":280,"end":281},"obj":"CVCL_6479|Finite_cell_line|Mus musculus"},{"id":"T3","span":{"begin":311,"end":312},"obj":"CVCL_6479|Finite_cell_line|Mus musculus"},{"id":"T4","span":{"begin":457,"end":461},"obj":"CVCL_0047|Telomerase_immortalized_cell_line|Homo sapiens"},{"id":"T5","span":{"begin":656,"end":658},"obj":"CVCL_5M23|Cancer_cell_line|Mesocricetus auratus"},{"id":"T6","span":{"begin":667,"end":668},"obj":"CVCL_6479|Finite_cell_line|Mus musculus"},{"id":"T7","span":{"begin":986,"end":1001},"obj":"CVCL_AZ81|Spontaneously_immortalized_cell_line|Sus scrofa"},{"id":"T8","span":{"begin":1108,"end":1115},"obj":"CVCL_0238|Cancer_cell_line|Homo sapiens"},{"id":"T9","span":{"begin":1165,"end":1166},"obj":"CVCL_6479|Finite_cell_line|Mus musculus"},{"id":"T10","span":{"begin":1201,"end":1208},"obj":"CVCL_0238|Cancer_cell_line|Homo sapiens"},{"id":"T11","span":{"begin":1364,"end":1365},"obj":"CVCL_6479|Finite_cell_line|Mus musculus"},{"id":"T12","span":{"begin":1501,"end":1504},"obj":"CVCL_Z424|Spontaneously_immortalized_cell_line|Ostrinia nubilalis"},{"id":"T13","span":{"begin":1522,"end":1523},"obj":"CVCL_6479|Finite_cell_line|Mus musculus"},{"id":"T14","span":{"begin":2145,"end":2146},"obj":"CVCL_6479|Finite_cell_line|Mus musculus"}],"text":"Robust augmented reality registration method for localization of solid organs' tumors using CT-derived virtual biomechanical model and fluorescent fiducials.\nBACKGROUND: Augmented reality (AR) is the fusion of computer-generated and real-time images. AR can be used in surgery as a navigation tool, by creating a patient-specific virtual model through 3D software manipulation of DICOM imaging (e.g., CT scan). The virtual model can be superimposed to real-time images enabling transparency visualization of internal anatomy and accurate localization of tumors. However, the 3D model is rigid and does not take into account inner structures' deformations. We present a concept of automated AR registration, while the organs undergo deformation during surgical manipulation, based on finite element modeling (FEM) coupled with optical imaging of fluorescent surface fiducials.\nMETHODS: Two 10 × 1 mm wires (pseudo-tumors) and six 10 × 0.9 mm fluorescent fiducials were placed in ex vivo porcine kidneys (n = 10). Biomechanical FEM-based models were generated from CT scan. Kidneys were deformed and the shape changes were identified by tracking the fiducials, using a near-infrared optical system. The changes were registered automatically with the virtual model, which was deformed accordingly. Accuracy of prediction of pseudo-tumors' location was evaluated with a CT scan in the deformed status (ground truth). In vivo: fluorescent fiducials were inserted under ultrasound guidance in the kidney of one pig, followed by a CT scan. The FEM-based virtual model was superimposed on laparoscopic images by automatic registration of the fiducials.\nRESULTS: Biomechanical models were successfully generated and accurately superimposed on optical images. The mean measured distance between the estimated tumor by biomechanical propagation and the scanned tumor (ground truth) was 0.84 ± 0.42 mm. All fiducials were successfully placed in in vivo kidney and well visualized in near-infrared mode enabling accurate automatic registration of the virtual model on the laparoscopic images.\nCONCLUSIONS: Our preliminary experiments showed the potential of a biomechanical model with fluorescent fiducials to propagate the deformation of solid organs' surface to their inner structures including tumors with good accuracy and automatized robust tracking."}

{"project":"GoldHamster","denotations":[{"id":"T1","span":{"begin":49,"end":61},"obj":"GO:0051179"},{"id":"T2","span":{"begin":79,"end":85},"obj":"D009369"},{"id":"T3","span":{"begin":79,"end":85},"obj":"D009369"},{"id":"T4","span":{"begin":200,"end":206},"obj":"SO:0000806"},{"id":"T5","span":{"begin":538,"end":550},"obj":"GO:0051179"},{"id":"T6","span":{"begin":554,"end":560},"obj":"D009369"},{"id":"T7","span":{"begin":554,"end":560},"obj":"D009369"},{"id":"T8","span":{"begin":790,"end":797},"obj":"UBERON:0000062"},{"id":"T9","span":{"begin":790,"end":797},"obj":"CHEBI:33250"},{"id":"T10","span":{"begin":913,"end":919},"obj":"D009369"},{"id":"T11","span":{"begin":913,"end":919},"obj":"D009369"},{"id":"T12","span":{"begin":1328,"end":1334},"obj":"D009369"},{"id":"T13","span":{"begin":1328,"end":1334},"obj":"D009369"},{"id":"T14","span":{"begin":1491,"end":1497},"obj":"UBERON:0002113"},{"id":"T16","span":{"begin":1505,"end":1508},"obj":"P30941"},{"id":"T15","span":{"begin":1505,"end":1508},"obj":"9823"},{"id":"T17","span":{"begin":1799,"end":1804},"obj":"D009369"},{"id":"T18","span":{"begin":1799,"end":1804},"obj":"D009369"},{"id":"T19","span":{"begin":1850,"end":1855},"obj":"D009369"},{"id":"T20","span":{"begin":1850,"end":1855},"obj":"D009369"},{"id":"T21","span":{"begin":1941,"end":1947},"obj":"UBERON:0002113"},{"id":"T22","span":{"begin":2284,"end":2290},"obj":"D009369"},{"id":"T23","span":{"begin":2284,"end":2290},"obj":"D009369"}],"text":"Robust augmented reality registration method for localization of solid organs' tumors using CT-derived virtual biomechanical model and fluorescent fiducials.\nBACKGROUND: Augmented reality (AR) is the fusion of computer-generated and real-time images. AR can be used in surgery as a navigation tool, by creating a patient-specific virtual model through 3D software manipulation of DICOM imaging (e.g., CT scan). The virtual model can be superimposed to real-time images enabling transparency visualization of internal anatomy and accurate localization of tumors. However, the 3D model is rigid and does not take into account inner structures' deformations. We present a concept of automated AR registration, while the organs undergo deformation during surgical manipulation, based on finite element modeling (FEM) coupled with optical imaging of fluorescent surface fiducials.\nMETHODS: Two 10 × 1 mm wires (pseudo-tumors) and six 10 × 0.9 mm fluorescent fiducials were placed in ex vivo porcine kidneys (n = 10). Biomechanical FEM-based models were generated from CT scan. Kidneys were deformed and the shape changes were identified by tracking the fiducials, using a near-infrared optical system. The changes were registered automatically with the virtual model, which was deformed accordingly. Accuracy of prediction of pseudo-tumors' location was evaluated with a CT scan in the deformed status (ground truth). In vivo: fluorescent fiducials were inserted under ultrasound guidance in the kidney of one pig, followed by a CT scan. The FEM-based virtual model was superimposed on laparoscopic images by automatic registration of the fiducials.\nRESULTS: Biomechanical models were successfully generated and accurately superimposed on optical images. The mean measured distance between the estimated tumor by biomechanical propagation and the scanned tumor (ground truth) was 0.84 ± 0.42 mm. All fiducials were successfully placed in in vivo kidney and well visualized in near-infrared mode enabling accurate automatic registration of the virtual model on the laparoscopic images.\nCONCLUSIONS: Our preliminary experiments showed the potential of a biomechanical model with fluorescent fiducials to propagate the deformation of solid organs' surface to their inner structures including tumors with good accuracy and automatized robust tracking."}