EP2384487A1 - Dispositif et procédé d'aide à la localisation cérébrale - Google Patents
Dispositif et procédé d'aide à la localisation cérébraleInfo
- Publication number
- EP2384487A1 EP2384487A1 EP10703314A EP10703314A EP2384487A1 EP 2384487 A1 EP2384487 A1 EP 2384487A1 EP 10703314 A EP10703314 A EP 10703314A EP 10703314 A EP10703314 A EP 10703314A EP 2384487 A1 EP2384487 A1 EP 2384487A1
- Authority
- EP
- European Patent Office
- Prior art keywords
- brain
- generic
- image
- converted
- transformation
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Ceased
Links
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/05—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/30—Determination of transform parameters for the alignment of images, i.e. image registration
- G06T7/35—Determination of transform parameters for the alignment of images, i.e. image registration using statistical methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/74—Image or video pattern matching; Proximity measures in feature spaces
- G06V10/75—Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video features; Coarse-fine approaches, e.g. multi-scale approaches; using context analysis; Selection of dictionaries
- G06V10/754—Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video features; Coarse-fine approaches, e.g. multi-scale approaches; using context analysis; Selection of dictionaries involving a deformation of the sample pattern or of the reference pattern; Elastic matching
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
- A61N2/00—Magnetotherapy
- A61N2/02—Magnetotherapy using magnetic fields produced by coils, including single turn loops or electromagnets
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10072—Tomographic images
- G06T2207/10088—Magnetic resonance imaging [MRI]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20016—Hierarchical, coarse-to-fine, multiscale or multiresolution image processing; Pyramid transform
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20112—Image segmentation details
- G06T2207/20128—Atlas-based segmentation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
- G06T2207/30016—Brain
Definitions
- the invention relates to a device for assisting the cerebral localization as well as a method of assisting the cerebral localization.
- the invention particularly allows an automatic location of the dorsolateral prefrontal cortex (DLPFC). This location finds its application, for example, in transcranial magnetic stimulation (TMS), electroencephalography or magnetoencephalography.
- DLPFC dorsolateral prefrontal cortex
- TMS transcranial magnetic stimulation
- electroencephalography magnetoencephalography
- Nuclear magnetic resonance imaging can be used to obtain two- or three-dimensional images (2D or 3D) of a chosen part of the human or animal body.
- MRI nuclear magnetic resonance imaging
- NMR nuclear magnetic resonance
- TMS transcranial magnetic stimulation
- Transcranial Magnetic Stimulation is a medical technique used in neurology, psychiatry and functional rehabilitation. It allows the treatment of disorders among which include epilepsy, migraine, depression or tinnitus.
- This technique makes it possible to stimulate a neuroanatomical zone such as the cerebral cortex painlessly and non-invasively.
- the stimulation is performed by means of a coil emitting short electromagnetic pulses.
- the location of a target neuroanatomical zone is generally performed by clinicians on images from medical imaging techniques such as MRI images for example. But this location is difficult to determine precisely and is directly dependent on the level of expertise of the clinician (neuroanatomist or neurosurgeon for example).
- TMS transcranial magnetic stimulation
- an apparatus called neuronavigator allows to identify in real time the stimulated zone of a subject of analysis (animal or human).
- the neuronavigator is generally calibrated on images recorded from a medical imaging device (including MRI apparatus).
- the imaging apparatus thus provides the necessary images of the brain of a subject of analysis.
- Positioning tools such as a band fixed around the head of the analysis subject and in communication with a binocular camera, then enable the real-time location of the effectively stimulated zone of the analysis subject.
- WO 2004/035135 A1 describes a method for three-dimensional modeling of a skull and internal structures thereof. This method is based on a correlation between the internal structures of a skull and its external dimensions. Thus, the method seeks to deduce the internal structure of a skull from simple dimensional measurements.
- EP 1 176558 A2 discloses an imaging system for superimposing image elements to obtain an improved image of a target anatomical region.
- the system uses surface dimensional measurements and a correlation with volumetric data acquired by x-ray.
- the computer tool Brainsight TM marketed by the company Rogue Research Inc. aims at a mapping between a brain mapping called "Talairach atlas" (Talairach & To ⁇ rnoux, 1988) and MRI image data of a subject of analysis.
- the mapping is performed by a geometric alignment implementing a coordinate registration.
- the present invention improves the situation by proposing an entirely different approach.
- the invention provides a computer device for aiding cerebral localization, comprising:
- a first memory arranged to store a generic three-dimensional cartography of at least a part of a brain, according to a first spatial localization mode, as well as for storing designation data, established according to the first spatial location mode, and corresponding to a target area of the brain in said mapping;
- a second memory arranged to receive and store a working image of at least a portion of the brain of an analysis subject acquired by medical imaging, this working image being stored according to a second spatial localization mode
- a non-rigid registration tool arranged to establish a registration transformation of the generic three-dimensional map to the work image
- a resampling tool for establishing, according to the registration transformation, a converted map, in the format of the second spatial location mode, as well as converted designation data
- a user interface arranged to form a visualization image, which corresponds, in part at least, to the work image and the cartography converted, while indicating in the visualization image a zone corresponding to the converted designation data.
- the invention also provides a method for assisting cerebral localization, the method comprising the following steps:
- vs. conduct electromagnetic wave imaging on at least part of the brain of a subject of analysis, to obtain a working image
- step d determining a target zone in the working image
- step f. presenting to an operator a representation of the target zone of step e., for an action on this target zone.
- FIG. 1 shows a schematic representation of a sagittal view of a human brain with indications of Brodmann areas
- FIG. 2 represents a schematic diagram of transcranial magnetic stimulation (TMS);
- FIG. 3 represents a computer device for aiding cerebral localization according to one embodiment of the invention
- FIG. 4 represents a block diagram of a non-rigid registration tool according to one embodiment of the invention
- FIG. 5 represents a functional diagram of a method for assisting the cerebral localization according to one embodiment of the invention.
- brain neuroanatomical areas including the dorsolateral prefrontal cortex.
- the invention is in no way limited to said zones but applies to any cerebral area accessible by medical imaging (such as for example the orbito- frontal cortex).
- DLPFC dorsolateral prefrontal cortex
- the prefrontal cortex gathers the lateral portions of areas 9-12, part of areas 45 and 46, and the upper portion of area 47 of
- the dorsolateral prefrontal cortex is a target area of the transcranial magnetic stimulation (TMS) technique.
- TMS transcranial magnetic stimulation
- one of the main applications of TMS is the treatment of the major depressive episode (depression) by repetitive high-frequency stimulation of the left dorsolateral prefrontal cortex (Gershon & al, 2003, Loo & Mitchell, 2005; & al, 2007).
- the latter must be previously located by a specialist clinician.
- the accuracy of this location is crucial to take full advantage of the TMS. But this location is manual, long, difficult and dependent on the level of expertise of the practicing clinician.
- a standardized method is applied initially proposed by George & al then Pascual-Leone et al.
- This method is based on Talairach's atlas (Talairach & Tournoux, 1988) and has been shown to be imprecise and not sufficiently taking into account the anatomical variability existing between different individuals. As a result, this may result in imprecise magnetic stimulations (Herwig & al, 2001).
- any clinician using a neuronavigator during a TMS must therefore in real time implement the standardized method described above to properly stimulate the target area.
- the positioning required is very fine; and the "field," that is, the brain to be examined, is not available in the form of a computer description of sufficient accuracy. This is why, until now, positioning is essentially defined by the operating clinician.
- the present invention greatly improves the state of the art and uses a non-rigid registration tool allowing a registration transformation between distinct images acquired by medical imaging (MRI in particular). This allows the computer device of the invention to automate the localization of a target area of the brain.
- Figure 2 shows a schematic diagram of the transcranial magnetic stimulation (TMS) technique.
- An analysis subject 200 for example an individual suffering from migraine or depression, is subjected to a magnetic field by an MRI apparatus 202 to obtain three-dimensional DJRM image data of his brain.
- the DJRM image data from the MRI apparatus 202 is transmitted to a neuronavigator 208.
- the subject of analysis and in direct interaction with a positioning system composed on the one hand, of a positioning tool 204 such as a band fixed around the head of the subject of analysis, and secondly a camera 206 in direct or indirect relationship with the positioning tool.
- the camera may in particular be a binocular camera.
- the interactions between analysis subject 200, positioning tool 204 and camera 206 form real-time data D_RT which are transmitted to neuronavigator 208.
- the real-time data D_RT consist of data D_RT01 coming from the positioning tool 204 and data D_RT02 from the camera 206.
- the real-time data set D_RT and DJRM image data form DataW job data as detailed below.
- the neuronavigator 208 connects the MRI image data DJRM and the real-time data D_RT. The neuronavigator 208 then transmits D_VISU display image data to a user interface 210.
- the interface 210 then represents a display image. It is by means of the visualization image that an operator can proceed to the positioning 212 of a coil 214 for emitting electromagnetic pulses.
- the real-time data D_RT from the interactions between analysis subject 200, positioning tool 204 and camera 206, allow the operator to adjust the positioning 212 of the coil 214 for each emitted electromagnetic pulse.
- the accuracy of adjustment is directly dependent on the operation of the neuronavigator as well as its implementations.
- the computer device for assisting the cerebral localization of the invention makes it possible to accurately follow, in real time, the zone effectively. stimulated by magnetic stimuli of TMS.
- the positioning of the TMS instruments in particular the winding 214, the positioning tool 204 and the camera 206, is adjusted with respect to the visualization images presented on the user interface 210.
- the device of the invention realizes a rigid registration of the space of the MRI images of the analysis subject with the space of the real-time data, by means of a geometrical transformation.
- This rigid registration is therefore done within the DataW work data, and more precisely between the DJRM image data and the real-time data D_RT.
- image space or "real-time data space” is meant a coordinate system or spatial location. This type of rigid alignment can in some cases be considered sufficient for the localization of deep structures (central gray nuclei, for example), but lacks precision for cortical structures with strong inter-individual anatomical variability ⁇ Hellier & al, 2003) .
- the registration tool not only provides the rigid registration described above, but also a registration of non-rigid nature.
- the Applicant has discovered not surprisingly that a non-rigid registration as described below, allows a precise, reproducible and automated location of a target area of a brain.
- the registration tool included in the device of the invention is arranged to use a non-rigid registration transformation. This transformation of non-rigid registration has previously been implemented by the Applicant. It is called "ROMEO"
- Locating spaces may include Cartesian coordinate systems (used in a vector space or affine space), curvilinear coordinate systems, cylindrical coordinate systems, spherical coordinate systems, and the like.
- the registration transformation of the invention estimates a dense field of geometric deformation between three-dimensional images.
- the transformation is based on the hypothesis of invariance of luminescence during the displacement of a physical point (robust statistical framework) - the so-called optical flow hypothesis (Horn & al,
- the multiresolution comprises: the hierarchical estimation of deformation fields on images derived from initial images by filtering and subsampling.
- multigrid is meant the estimation of deformations on a sequence of nested spaces, namely starting from a level of coarsest resolution towards a level of finest resolution.
- Each space is defined by a piece-wise parameterization based on a spatial partition of the volume.
- the multi-grid spaces are nested, since the spatial partitions are nested (that is, the transition to a finer grid level corresponds to an adaptive subdivision of the spatial partition).
- each grid level corresponds to a partition, and when one goes to the finer grid level, the spatial partition is adaptively cut.
- FIG. 3 relates to the invention and shows a computer device for aiding cerebral localization 300 according to one embodiment of the invention.
- the device 300 comprises a first memory 302 capable of storing data, for example a RAM (Random Access Memory) type memory.
- This first memory 302 is arranged to store a generic three-dimensional mapping of at least a portion of a brain.
- this generic three-dimensional mapping is established by an expert in neuroanatomy on a brain image recorded by magnetic resonance imaging (MRI).
- MRI magnetic resonance imaging
- the brain referred to at this stage is a brain that can be described as a model brain or a generic brain.
- the generic three-dimensional mapping is stored in the first memory 302 according to a first spatial location mode (or coordinate system).
- Generic three-dimensional mapping includes the localization of areas of interest such as, for example, the dorsolateral prefrontal cortex (DLPFC) or the orbito-frontal cortex.
- the first memory 302 can therefore also store precise designation data. These designation data correspond to a target area of the brain and are generally stored in the same spatial location mode as generic three-dimensional mapping.
- the target area of the brain can be chosen in particular depending on the targeted treatment. For example, for treatment of depressions the target area will be the dorsolateral prefrontal cortex (DLPFC).
- the cerebral localization assistance computer device 300 includes a second memory 304 capable of storing data (RAM type).
- the second memory 304 is arranged to receive and store a working image of at least a portion of the brain of a subject of analysis (such as for example a patient for disorders of depressions).
- the work picture is acquired by medical imaging as magnetic resonance imaging (MRI), just like generic three-dimensional mapping, but according to a second precise spatial localization mode that is generally not identical to that of mapping (because it may be MRI distinct or different modes of acquisition sequences).
- MRI magnetic resonance imaging
- the two spatial location modes are not necessarily distinct.
- the working image is stored in a second spatial location mode.
- the computing device 300 comprises a non-rigid registration tool 306 which receives generic DataGen three-dimensional mapping data and data data DataW respectively from the first memory 302 and the second memory 304. It is from these data ( DataGen and DataW) that the non-rigid registration tool 306 establishes a registration transformation of the generic three-dimensional mapping to the work image.
- the image data (working image) directly from the analysis subject can then be resampled into the coordinate system of the generic three-dimensional cartography.
- FIG. 4 shows a functional diagram of the non-rigid registration tool 306.
- a rigid registration operation 3061 acts on the data data DataW by performing a rigid registration as described above, namely a rigid registration between the DJRM image data and the real-time data D_RT.
- the rigid registration operation provides a DataWrec recalibrated work data, corresponding to the transformation of the DJRM IRM image data to the D_RT real-time data (or vice versa).
- the rigid registration of the operation 3061 uses a statistical method called "maximizing the mutual information" (Maes & al, 1997).
- a non-rigid registration operation 3062 then performs a non-rigid registration of the generic DataGen three-dimensional mapping data to the DataWrec (or vice versa) recalibrated work data.
- the non-rigid registration operation 3062 uses the non-rigid ROMEO registration transformation described above.
- the registration tool 306 therefore implements a computer program for establishing a non-rigid registration transformation by the ROMEO method.
- the non-rigid registration tool 306 provides DataT transformation data substantially representing the registration transformation of the generic three-dimensional mapping to the work image.
- the application of the registration transformation is carried out by a resampling tool 308 shown in FIG. 3.
- the resampling tool 308 established according to the DataT registration transformation a converted cartography, in the format of the second mode of spatial location of the work image.
- the DataT resetting transformation established by the resetting tool 306 is applied to the data data DataW (corresponding to the working image) to give a converted cartography according to the second spatial localization mode.
- the resampling tool 308 outputs D-VISU visualization data allowing "mapping" of the generic three-dimensional mapping to the working image (DataW :: DataGen). This "mapping" corresponds substantially to said converted map. Accordingly, the resampling tool 308 establishes converted designation data to retrieve a target area (detailed below). The converted designation data then substantially correspond to the designation data of the target area of the brain previously determined on the generic three-dimensional map.
- the computing device 300 further comprises a user interface 310, arranged to form a display image.
- This visualization image is formed from the visualization data D-VISU and at least partially matches the working image and the converted cartography, while indicating, in the visualization image, an area corresponding to the converted designation data.
- FIG. 5 is a block diagram of a cerebral localization assisting method according to an embodiment of the invention.
- a first generic image acquisition operation 500 makes it possible to obtain a generic image of a brain. This operation generally involves conducting electromagnetic wave imaging on the brain of a reference subject, for example by MRI. The generic image of the brain thus obtained is used in a generic mapping acquisition operation 502 to establish a generic three-dimensional map from said generic brain image. These two operations (500 and 502) once performed may be unique for any embodiment of the method of the invention. Indeed, once the generic mapping is established, it can be used for any embodiment of the method of the invention.
- the next target area designation operation on the generic mapping 504 is to prepare a designation of a brain area on said generic three-dimensional map.
- a job image acquisition operation 506 involves conducting electromagnetic wave imaging on at least a portion of the brain of a subject of analysis. This operation 506 makes it possible to obtain a working image.
- a non-rigid registration operation 508 applies a non-rigid registration of the generic three-dimensional mapping to the working image, to obtain a spatial geometric transformation for moving from the generic three-dimensional map to said work image acquired during the job image acquisition operation 506.
- a conversion operation 510 then establishes a converted map for the job image.
- a target area location operation 512 determines the target area in the working image (especially thanks to the conversion operation 510).
- a display image forming operation 514 consists in presenting to an operator a representation of the target zone, with a view to an action on this targeted zone. The action may in particular be a transcranial magnetic stimulation.
- DLPFC dorsolateral prefrontal cortex
- Table 1 shows the comparative analysis between the invention and the state of the art.
- the results of the table show the inter-variability between the results of the manual localization of the dorsolateral prefrontal cortex (DLPFC) performed by the clinicians (columns: clinician 1, clinician 2 and clinician 3).
- DLPFC dorsolateral prefrontal cortex
- the method for aiding cerebral localization with a non-rigid registration provides better results compared to the rigid registration method (column: rigid) of the prior art.
- a rigid registration as known in the state of the art has 6 degrees of freedom.
- the non-rigid registration relative to the invention has about 40 million degrees of freedom.
- the accuracy of a neuronavigation system is about 2mm.
- the target area is precisely set to NRM. It can be seen that clinicians could make errors of more than 10mm in the localization of this target area, which considerably degrades the accuracy of TMS stimulations.
- the average error of clinicians is about 1 cm which is favorable to optimal use of a neuronavigator.
- the invention allows clinicians to overcome the manual location.
- the method of assisting localization and the device of the invention is more accurate than can be the manual location by a clinician.
- the invention is reproducible. To achieve this, it was necessary to ensure the anatomical coherence of the deformations observed when passing from one subject to another. To ensure this consistency, at a sufficient level, the estimated deformation field should be regularized. The adjustment of this regularization is particularly difficult in the absence of "ground truth" (we do not know the "true” field of deformation between the brains of two different subjects). It is therefore impossible to have absolute criteria to validate the registration techniques. This is why the precision and reproducibility obtained here are important.
Abstract
Description
Claims
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
FR0900254A FR2941315B1 (fr) | 2009-01-21 | 2009-01-21 | Dispositif et procede d'aide a la localisation cerebrale |
PCT/FR2010/000033 WO2010084262A1 (fr) | 2009-01-21 | 2010-01-15 | Dispositif et procédé d'aide à la localisation cérébrale |
Publications (1)
Publication Number | Publication Date |
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EP2384487A1 true EP2384487A1 (fr) | 2011-11-09 |
Family
ID=40688374
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
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EP10703314A Ceased EP2384487A1 (fr) | 2009-01-21 | 2010-01-15 | Dispositif et procédé d'aide à la localisation cérébrale |
Country Status (4)
Country | Link |
---|---|
US (1) | US20120087559A1 (fr) |
EP (1) | EP2384487A1 (fr) |
FR (1) | FR2941315B1 (fr) |
WO (1) | WO2010084262A1 (fr) |
Families Citing this family (6)
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FR2970638B1 (fr) * | 2011-01-26 | 2014-03-07 | Inst Nat Rech Inf Automat | Procede et systeme d'aide au positionnement d'un outil medical sur la tete d'un sujet |
JP6242787B2 (ja) * | 2011-06-03 | 2017-12-06 | ネクスティム オーワイジェイ | 解剖学的接続性パターンと誘導脳刺激とを組み合せるシステム |
US9091628B2 (en) | 2012-12-21 | 2015-07-28 | L-3 Communications Security And Detection Systems, Inc. | 3D mapping with two orthogonal imaging views |
US11311193B2 (en) * | 2017-03-30 | 2022-04-26 | The Trustees Of Columbia University In The City Of New York | System, method and computer-accessible medium for predicting response to electroconvulsive therapy based on brain functional connectivity patterns |
CN108187230A (zh) * | 2018-01-29 | 2018-06-22 | 上海理禾医疗技术有限公司 | 经颅磁刺激导航定位机器人系统及定位方法 |
US11779218B2 (en) * | 2020-05-18 | 2023-10-10 | The Trustees Of Columbia University In The City Of New York | System, method and computer-accessible medium for predicting response to electroconvulsice therapy based on brain functional connectivity patterns |
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US6594516B1 (en) | 2000-07-18 | 2003-07-15 | Koninklijke Philips Electronics, N.V. | External patient contouring |
FI113615B (fi) | 2002-10-17 | 2004-05-31 | Nexstim Oy | Kallonmuodon ja sisällön kolmiulotteinen mallinnusmenetelmä |
US8160677B2 (en) * | 2006-09-08 | 2012-04-17 | Medtronic, Inc. | Method for identification of anatomical landmarks |
-
2009
- 2009-01-21 FR FR0900254A patent/FR2941315B1/fr active Active
-
2010
- 2010-01-15 WO PCT/FR2010/000033 patent/WO2010084262A1/fr active Application Filing
- 2010-01-15 US US13/145,547 patent/US20120087559A1/en not_active Abandoned
- 2010-01-15 EP EP10703314A patent/EP2384487A1/fr not_active Ceased
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Also Published As
Publication number | Publication date |
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US20120087559A1 (en) | 2012-04-12 |
FR2941315B1 (fr) | 2014-12-05 |
WO2010084262A1 (fr) | 2010-07-29 |
FR2941315A1 (fr) | 2010-07-23 |
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Effective date: 20200706 |