The Experts below are selected from a list of 51 Experts worldwide ranked by ideXlab platform
Letterio S Politi - One of the best experts on this subject based on the ideXlab platform.
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development and validation of a new mri simulation technique that can reliably estimate optimal in vivo Scanning Parameters in a glioblastoma murine model
PLOS ONE, 2018Co-Authors: Andrea Protti, Kristen Jones, Dennis M Bonal, Lei Qin, Letterio S Politi, Sasha Kravets, Quangde Nguyen, Annick D Van Den AbbeeleAbstract:Background Magnetic Resonance Imaging (MRI) relies on optimal Scanning Parameters to achieve maximal signal-to-noise ratio (SNR) and high contrast-to-noise ratio (CNR) between tissues resulting in high quality images. The optimization of such Parameters is often laborious, time consuming, and user-dependent, making harmonization of imaging Parameters a difficult task. In this report, we aim to develop and validate a computer simulation technique that can reliably provide "optimal in vivo Scanning Parameters" ready to be used for in vivo evaluation of disease models. Methods A glioblastoma murine model was investigated using several MRI imaging methods. Such MRI methods underwent a simulated and an in vivo Scanning Parameter optimization in pre- and post-contrast conditions that involved the investigation of tumor, brain parenchyma and cerebrospinal fluid (CSF) CNR values in addition to the time relaxation values of the related tissues. The CNR tissues information were analyzed and the derived Scanning Parameters compared in order to validate the simulated methodology as a reliable technique for "optimal in vivo Scanning Parameters" estimation. Results The CNRs and the related Scanning Parameters were better correlated when spin-echo-based sequences were used rather than the gradient-echo-based sequences due to augmented inhomogeneity artifacts affecting the latter methods. "Optimal in vivo Scanning Parameters" were generated successfully by the simulations after initial Scanning Parameter adjustments that conformed to some of the Parameters derived from the in vivo experiment. Conclusion Scanning Parameter optimization using the computer simulation was shown to be a valid surrogate to the in vivo approach in a glioblastoma murine model yielding in a better delineation and differentiation of the tumor from the contralateral hemisphere. In addition to drastically reducing the time invested in choosing optimal Scanning Parameters when compared to an in vivo approach, this simulation program could also be used to harmonize MRI acquisition Parameters across scanners from different vendors.
Gauthier Rathat - One of the best experts on this subject based on the ideXlab platform.
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Surgery of nonpalpable breast cancer: First step to a virtual per‐operative localization? First step to virtual breast cancer localization
Breast Journal, 2019Co-Authors: Martha Duraes, Patrice Crochet, Emmanuelle Pagès, Elsa Grauby, Lidia Lasch, Lucie Rebel, Frederick Van Meer, Gauthier RathatAbstract:Introduction: Preoperative localization procedures of occult breast cancer (radioisotopic and wire localization) are invasive and uncomfortable. We have evaluated a novel technique which allows a virtual localization. Material and methods: Our retrospective study focused on patients treated for occult and unifocal breast cancer from September 2016 to June 2017. All patients had radioisotopic preoperative localization. We included patients who had a preoperative prone Magnetic Resonance Imaging (MRI) and an intraoperative 3D optical scan. During surgery, the surgeon localized the tumor thanks to a gamma detection probe and marked the localization on the skin with a black marker. The breast was then optically scanned. MRI was adjusted to the optical surface to match the exact breast position in the Operating Room. The virtual localization provided by the 3D breast modeling tool was retrospectively compared with the radioisotopic localization, defined as the pen mark visible in the optical scan. Results: Nine patients were included in this feasibility study. Tumors were successfully localized in the respective breast quadrant. The mean cutaneous distance between virtual and radioisotopic localization was 1.4 cm in patients with low breast volume (5/9) and 2.8 cm in those with large breast volume (4/9). Conclusion: We developed a research prototype which enables virtual preoperative localization of nonpalpable breast lesions using MRI images and intraoperative optical Scanning. Parameter optimization is required and will lead to a precise and noninvasive tool. By adding augmented reality, it will be possible to initiate a prospective study to compare this tool with the traditional localizations.
Annick D Van Den Abbeele - One of the best experts on this subject based on the ideXlab platform.
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development and validation of a new mri simulation technique that can reliably estimate optimal in vivo Scanning Parameters in a glioblastoma murine model
PLOS ONE, 2018Co-Authors: Andrea Protti, Kristen Jones, Dennis M Bonal, Lei Qin, Letterio S Politi, Sasha Kravets, Quangde Nguyen, Annick D Van Den AbbeeleAbstract:Background Magnetic Resonance Imaging (MRI) relies on optimal Scanning Parameters to achieve maximal signal-to-noise ratio (SNR) and high contrast-to-noise ratio (CNR) between tissues resulting in high quality images. The optimization of such Parameters is often laborious, time consuming, and user-dependent, making harmonization of imaging Parameters a difficult task. In this report, we aim to develop and validate a computer simulation technique that can reliably provide "optimal in vivo Scanning Parameters" ready to be used for in vivo evaluation of disease models. Methods A glioblastoma murine model was investigated using several MRI imaging methods. Such MRI methods underwent a simulated and an in vivo Scanning Parameter optimization in pre- and post-contrast conditions that involved the investigation of tumor, brain parenchyma and cerebrospinal fluid (CSF) CNR values in addition to the time relaxation values of the related tissues. The CNR tissues information were analyzed and the derived Scanning Parameters compared in order to validate the simulated methodology as a reliable technique for "optimal in vivo Scanning Parameters" estimation. Results The CNRs and the related Scanning Parameters were better correlated when spin-echo-based sequences were used rather than the gradient-echo-based sequences due to augmented inhomogeneity artifacts affecting the latter methods. "Optimal in vivo Scanning Parameters" were generated successfully by the simulations after initial Scanning Parameter adjustments that conformed to some of the Parameters derived from the in vivo experiment. Conclusion Scanning Parameter optimization using the computer simulation was shown to be a valid surrogate to the in vivo approach in a glioblastoma murine model yielding in a better delineation and differentiation of the tumor from the contralateral hemisphere. In addition to drastically reducing the time invested in choosing optimal Scanning Parameters when compared to an in vivo approach, this simulation program could also be used to harmonize MRI acquisition Parameters across scanners from different vendors.
Martha Duraes - One of the best experts on this subject based on the ideXlab platform.
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Surgery of nonpalpable breast cancer: First step to a virtual per‐operative localization? First step to virtual breast cancer localization
Breast Journal, 2019Co-Authors: Martha Duraes, Patrice Crochet, Emmanuelle Pagès, Elsa Grauby, Lidia Lasch, Lucie Rebel, Frederick Van Meer, Gauthier RathatAbstract:Introduction: Preoperative localization procedures of occult breast cancer (radioisotopic and wire localization) are invasive and uncomfortable. We have evaluated a novel technique which allows a virtual localization. Material and methods: Our retrospective study focused on patients treated for occult and unifocal breast cancer from September 2016 to June 2017. All patients had radioisotopic preoperative localization. We included patients who had a preoperative prone Magnetic Resonance Imaging (MRI) and an intraoperative 3D optical scan. During surgery, the surgeon localized the tumor thanks to a gamma detection probe and marked the localization on the skin with a black marker. The breast was then optically scanned. MRI was adjusted to the optical surface to match the exact breast position in the Operating Room. The virtual localization provided by the 3D breast modeling tool was retrospectively compared with the radioisotopic localization, defined as the pen mark visible in the optical scan. Results: Nine patients were included in this feasibility study. Tumors were successfully localized in the respective breast quadrant. The mean cutaneous distance between virtual and radioisotopic localization was 1.4 cm in patients with low breast volume (5/9) and 2.8 cm in those with large breast volume (4/9). Conclusion: We developed a research prototype which enables virtual preoperative localization of nonpalpable breast lesions using MRI images and intraoperative optical Scanning. Parameter optimization is required and will lead to a precise and noninvasive tool. By adding augmented reality, it will be possible to initiate a prospective study to compare this tool with the traditional localizations.
Andrea Protti - One of the best experts on this subject based on the ideXlab platform.
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development and validation of a new mri simulation technique that can reliably estimate optimal in vivo Scanning Parameters in a glioblastoma murine model
PLOS ONE, 2018Co-Authors: Andrea Protti, Kristen Jones, Dennis M Bonal, Lei Qin, Letterio S Politi, Sasha Kravets, Quangde Nguyen, Annick D Van Den AbbeeleAbstract:Background Magnetic Resonance Imaging (MRI) relies on optimal Scanning Parameters to achieve maximal signal-to-noise ratio (SNR) and high contrast-to-noise ratio (CNR) between tissues resulting in high quality images. The optimization of such Parameters is often laborious, time consuming, and user-dependent, making harmonization of imaging Parameters a difficult task. In this report, we aim to develop and validate a computer simulation technique that can reliably provide "optimal in vivo Scanning Parameters" ready to be used for in vivo evaluation of disease models. Methods A glioblastoma murine model was investigated using several MRI imaging methods. Such MRI methods underwent a simulated and an in vivo Scanning Parameter optimization in pre- and post-contrast conditions that involved the investigation of tumor, brain parenchyma and cerebrospinal fluid (CSF) CNR values in addition to the time relaxation values of the related tissues. The CNR tissues information were analyzed and the derived Scanning Parameters compared in order to validate the simulated methodology as a reliable technique for "optimal in vivo Scanning Parameters" estimation. Results The CNRs and the related Scanning Parameters were better correlated when spin-echo-based sequences were used rather than the gradient-echo-based sequences due to augmented inhomogeneity artifacts affecting the latter methods. "Optimal in vivo Scanning Parameters" were generated successfully by the simulations after initial Scanning Parameter adjustments that conformed to some of the Parameters derived from the in vivo experiment. Conclusion Scanning Parameter optimization using the computer simulation was shown to be a valid surrogate to the in vivo approach in a glioblastoma murine model yielding in a better delineation and differentiation of the tumor from the contralateral hemisphere. In addition to drastically reducing the time invested in choosing optimal Scanning Parameters when compared to an in vivo approach, this simulation program could also be used to harmonize MRI acquisition Parameters across scanners from different vendors.
